{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to the Ideal Binary Mask"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### This file uses two speech files as an input, and uses an Ideal Binary Mask to separate them again. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import signal\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.io import wavfile\n",
    "import numpy as np\n",
    "from math import ceil\n",
    "import sounddevice as sd\n",
    "from sphfile import SPHFile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"./SA1.wav\"\n",
    "file2 = \"./SA2.wav\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Transfer SPHFile to wav"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'SA1.wav'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sph1 = SPHFile('TIMIT/SA1.WAV')\n",
    "sph1.write_wav('SA1.wav')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'SA2.wav'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sph2 = SPHFile('TIMIT/SA2.WAV')\n",
    "sph2.write_wav('SA2.wav')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. The two speech files are both padded with zeros to make them the same length, and further padded to pad the length to the nearest whole second. This was done to make implementing the STFT and iSTFT easier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read 2 wav files; rate:16000Hz; samples:not belong to [0,1]\n",
    "sample_rate1, samples1 = wavfile.read(file1)\n",
    "sample_rate2, samples2 = wavfile.read(file2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find length of longest signal\n",
    "maxlength = max(len(samples1),len(samples1))  # 53556\n",
    "\n",
    "# Pad each signal to the length of the longest signal\n",
    "samples1 = np.pad(samples1, (0, maxlength - len(samples1)), 'constant', constant_values=(0))\n",
    "samples2 = np.pad(samples2, (0, maxlength - len(samples2)), 'constant', constant_values=(0))\n",
    "\n",
    "# Combine series together\n",
    "mixed_series = samples1 + samples2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Play the mixed speech\n",
    "sd.play(mixed_series, sample_rate1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pad 3 wav files to whole number of seconds\n",
    "extrapadding = ceil(len(mixed_series) / sample_rate1) * sample_rate1 - len(mixed_series)\n",
    "mixed_series = np.pad(mixed_series, (0, extrapadding), 'constant', constant_values=(0))\n",
    "samples1 = np.pad(samples1, (0,extrapadding), 'constant', constant_values=(0))\n",
    "samples2 = np.pad(samples2, (0,extrapadding), 'constant', constant_values=(0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Play and save the mixed speech\n",
    "sd.play(mixed_series, sample_rate1)\n",
    "#wavfile.write('mixed.wav', sample_rate1, np.asarray(mixed_series, dtype=np.int16))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show 3 wav files in plot\n",
    "x = np.arange(0, (len(mixed_series) / sample_rate1), (1 / sample_rate1))\n",
    "\n",
    "#Show wav file on chart\n",
    "fig = plt.figure()\n",
    "fig, (ax1, ax2) = plt.subplots(2, figsize=(6,5), sharey=True)\n",
    "\n",
    "ax1.plot(x, mixed_series, color=\"green\", alpha = 0.8)\n",
    "ax1.set(title='Mixture wav files', ylabel='Amplitude')\n",
    "ax1.legend(['Combined signals'])\n",
    "\n",
    "ax2.plot(x, samples1, color=\"blue\", alpha = 0.5)\n",
    "ax2.plot(x, samples2, color=\"red\", alpha = 0.5)\n",
    "ax2.set(xlabel='Time [sec]', ylabel='Amplitude')\n",
    "ax2.legend(['Signal 1', 'Signal 2'])\n",
    "\n",
    "#fig.savefig(\"mixturesignals.png\", bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "plt.close(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute the STFT of the 3 wav files\n",
    "nperseg = sample_rate1 / 50  # Length of each segment. Defaults to 256. Set to 0.05 of a second\n",
    "\n",
    "#Get stft of 3 wav files\n",
    "f1, t1, Zsamples1 = signal.stft(samples1, fs=sample_rate1, nperseg=nperseg)\n",
    "f2, t2, Zsamples2 = signal.stft(samples2, fs=sample_rate1, nperseg=nperseg)\n",
    "fmixed, tmixed, Zmixed_series = signal.stft(mixed_series, fs=sample_rate1, nperseg=nperseg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Q5oD+YNatvtauDeHmZrYeWpPOVB3Q6fXawFiPO+Nz72vqvQCLy/tknBQzFmtci50t1BV98hUHk8OSJavUUiY/pGvJ2mG0+cbJ5/voc5cBlAH9oCyDRI1Ui71Fe1fJvKCU/2+O3Re5M/zjJn2o2+embbZFkLn+oJ9PJ+tXx8/JFt7RhXhMPv1e06luir5kPWwM9xaXd1YqsRyXcWFtPtaugoVqwFiqKIrSBVl/7vZnV3CLFPSaGzrg4qCEc14ld2ZTuIsx5luK90nu9sJdHqzH5wNdBJaj43ne9MUo8DowTy4W1nOzV+OiwyC9zLwSNod7i0v9ZIoWmUwAi3+8ayXdxqB2LMpWKFmVm7bK6T4IV5ughSrs6rft06R8SbBuLO+U0qDlft/krpdNQ9MFO8jK/sPJOLRPzyuTFSrWpdtNYK723OxyI9oL3E3BHswhAdW4vE9oTZo1/zM3ynYbkaeWi+VMbpwkyhUVOTvZHZasNEEWmYm3676ESeRiwaRw8mWoxPVv+X4mpeAO3K57JXcm7Z1R1I0C0ZUlKvAiLy6MVbYFOgmmtt1x6HmJVAqxIIjJ5OIpxgZ7tEEJWI/LPQuaXZy/GKxLP1V2TFu43GMnH2R6SbUg8nyeKhS7dLPqqF4bcXyeERSCraEyQDZ7YM6luZO0SCZjxD7InaFZmYAhkyt2X/n8AbvHume5w7nPeEHkYqGCYJMEoIIN9J6gM8XdxFPsMI4hYD0up1ZgFucid0edIL2+JhRHUNxIdTehOC9XYMnWHWXP2yUdwc/y0WXb20KYpLYDf2Gow43UmSx2ZVUiQTZ7xV7InbOx74V6Ety/FxJdUHK6lEHjFTVtivFIfb5apfSLi4Cy3xH4x3uPy/l0HGWuVtEPSguFZCxafQ5uJ3DBpXi42TfMwr22/33AcMX6SureZ9aCgN3DC9ApO8YNBN3JguIGxrpy1zYf6qbwghzJpXp0lU0iyN3Fg9lM+fLTUJ66pDj5XkeKIpXR4uCgs2t0CUsnbDoHlclSkLG9x+VUkE2qpqLdcMmgtRG1LJVSWiUkGy7ibiCe3zcxHFoqg61CZ/q1IyuWm01DTCadtw8g7LAvGhouFtaTkiTpZnDLyBQJ8ip+7aAzGYW480j/IHcXD25qwiI0yHctl6v8x27e4qZdiwdAHENMxpDTKeJ77gYiATmdgsajvaLu2ViEMt2hUWNBOT4PuJyzYEG6tLXH+27HrrlDvrvUTSmjJyazOOdyD+9Q2NJI5JaWhbIFOUwkFw9Uszy5lrFd50M1Vtq9krt4kNJO+rD4BprFxYEzNlrJUseyaKlLiyVI6LVOsgrYm0xSfv0+oit5C+vbXuNyz4DGAuOibsGCHvpi2jcTBwlKo9T1MdYNNRxat++uYKL5Vf7Klta9kuwhARcQDZUvY601gavbhsmesTdyZ67t8rm7RJC7iwWH5y/3TOkkY5EdjZSXaLGAnE4BAHI237uxaLzH+xpEGNAtLreCbBaYOou1m2FCUC8BQ34QhaJPOFxD9eFm5WX7gA4apCjqz/0drFgXC003mC05k61hMlhsWta5a+j+yMUiXaT7ykG+Z8pJQDv0RgtqMU4oVrmO5ckpxOGhyhQDgOVuA3NL0ZVyTN0UHAnoF5de+8gN0rIUb07k/Vpe1IYThssrtnQKXUXPzWrhHrtLBbLTPgRF+HLAddPW8dY4AbUXbsy36IO7kd41BSVgz+FSLPZJKSOB5ORUvRakjEFmAzidKfrFHllqjQGrq43yVoL9A1rhcj+ZuopsQTGRSsHdNEhPB+G5vEJepdWFbDDEPpS7ddLw8GoZghYCaqN2Ra+igLFt5w11PUxG7nZMa8rI3r6UnA7YXzhem0zWkw1QONZatCcmYyVXROD5HDQeAYm2HrcI/usDnCROrub2qpMNeAxr397icivIJiq3QRRv4euOYC3Imn/MklXeY4f3RO5Ou4to2k1hFPgkCYt0QGM0zr6w45yh5Fm4drk5dTPqbH3DEHCuYTnIJgi8i81em/GXSNBwCDmdqQA9KUFXJpunVOsRxpsLoL3MGU/aHv2+gDwu79NxU9804CBbC04Vd7kNJ8uxEFEUgQaxsiw7rl1eLNNr7EjI3BLA/V4oLP6XGo6c7mRBcTaieyN3hubVJ48xyN2FQSZ+ZTi0rwF0QmFo0wavlkCUBuAmJ6eAtqx2Udikc3Qk8xk9ImBvcXkVZK3g1nb3mnOA1JrVx+A2VmGtFPBikeUbmp01tCVphxytTLGCgIC62EB2jJdiJ2PN0Bn2RO50J9T/YIEKWAOXs97IY+qj6zWPpaJROBmQxCC2Oc/3zSvZJWc411aQ473EpX4qJAhiNK4XLKRhymN2rhy7lem0dcj9byrq2d227v8uJxGXL91bhH+YOC4W3AWhrtw5QbK9jPd1/WAJOBH1u5a7HPrKYhFk72KBhOL8tmyjM5AADQfg5SrlIsex8tTs4dgz1KYuNuk2EN8JQg7YP+zfKNwWtPW4lrJbVChEt1HWdhtkyko7dA71Wpe8dWgYu4LpQydcsT2cEAN6gllkasrdriPvKR4Ack/kzqukF7w3AXVgqTluvvqmSlnJ8ZsG07neUAxUujckEuLKwc5lPgcSebpjC+xTdo6AclxerYSb51kURoh76o/bL1eAKB6oz4dDlUhdR9LuUshIkJowDE+s64XaUQICLgg2cScaDnA8sHLQOSraNEqx3BO5c/vUC9XLlbsgexcLWsnrvtkN536WwEpTPiSDpfKQmtz/YhDvl6fGpF7tIruGyYQVDEN7jcv5dFz3Yc1FwCyS5nVlBHALjpdZgE1aN7lY2CwW5hirqK9LN9cjOEnAy1Xa55YVmgoDsIKb92JBy0WTBZUEWZngJNm6ZcnwISmK9kLurLyZfOirHtzRrtwF+Tv/cJ6nmbM3RsHaZtOVNW6KIa4fKWoFM0gIiMMrSG7fgVwsQAcH++MhMTFLqyXoyqQTj6nd8AcZ21tc2idjFLJapTcNHxjIWJC63t1ykkAMh6l1yJRxlpypVGcDlgz9YheWHpN2TisNbe9FadqvYMW6OPB59jWON+Wde+Ugr+uGVsr3Qu6AlPNvqFd9KBGBG3mx4I7XllmWOgNL8HQGcfUQPJ2qdTWRiO+9oazHe1YWm5NElcZeLDuROXI23AH7icupIDsLbS2BN5Yvc2xPi6NRhsksfu41SbmeeLW0eZLdggHbhpkgOrWk7bIgRED/MHJXl1e8DxsmEoAupW49OzuUOwCZNG+du2kduds7HmjAZnAynrQJ0isd9xvKJA2HVilWFtUYcjpVFIsoAlarndOZXCivbgxerrqRDaK9+n0BeVxOBVnDumxrLDBmYcxw/7ruj4lsNYU3tPCYDBEkVHCQyWXZKmVPW+hAJbPL78WKFVxPFxc1XYskCNIsSDt0+xuKBbBbubPWbMOHFD0ssj0XRArYDdbO0WuedZmXb2NlMUkAZsjpFDQcQJ6dgYSAPD5Rn41GezX+LJUk6mD9Zwkw79XvC8jjUj+dJqnJKIqsgKxNYL7poNeTj1wssm7dJFF9NQp67PR7VwJm8jQ71JMu2swhcCEvFgyXryZVwndBbt2qqQOIQGJv5M7QKixvvw9l3VinAy4GvFzehVi3aS2hOG0qk3K5UtZY4aZ+JIAZ0dGRymyxLxxk6Kwb8zmQdBCDEILQzwV6neWJ6DoRvYGI3klE7yCiTyGiu4no54noXfr/XfpYIqLvJqJ3E9HvE9GznXZeqI9/FxG9sJPOuZWE1gxSm1WCndLKfeVC1uUsSZBakPWkxJLznKyy9HNbgLkHhn/cWnEpc6eb3xcmkouHunIHJ03VtjnI5JR4N9ix3GXoTX30Y4e/L6BHkMimeSv4fu08W/D9psqiWec4SUDjkW2LFwtASmC52p8sFloW5HKl4oFarkeZ+STI2d6i7yfzXQD+H2b+KAAfB+AdAP45gF9k5mcC+EX9HgA+B8Az9d+LAXwPABDR3QC+AcAnA/gkAN9glOqNoSkSVvhquJYyk8AGk0itbjk5j1m7n0gH7ZEgyNlcBRUmaYqYnU0gRnF3lOQ2KFWww+RxceCnEKspd5mxsWVuulnA5XK1X3JnrNo9WpD3yXoX0BJdyE1J/u+NZcF4ZZIE8uQUJAhiMlEpHccjyOmsXX97gBjEnck/b5j9I2B76E37IKJrAP4ygFcBADMvmPkWgOcBeLU+7NUAnq9fPw/AD7HCmwBcJ6InAfgsAD/PzDeZ+XEAPw/gs1t30J0s6iq8dQuFbAjSeR9tGidPCKMrB6o7+vtdZ7EwxR66sKbbBd+7RsAFg0uZqSl3O60WqTPLmNf7IHeqM06RkD7SvGG39z2gW9gqkMOKHL515LHLID1B4MVSbzopNQwZq/KeUSwMOskl7c5/wTu6t+hTA3k6gEcA/AARvZWIvp+IrgB4AjM/CAD6/336+PsBvM85/wH9WdnnGRDRi4noLUT0liXmaztn85kWLQJFk4C7sLflD5UtaHrxzUwK2r3LJpE6kLp8TTaAXfB0tWJM8aCTMtOlldWa3uMu7kFQzBuhiexZb0Pd52oWki4CYzc53+Hi7ovcuTzu3njCu1q8g+zVRm25MxbPKopFnftexkvf8JnRZKL+RxFoPIK4dqi8ppOxSqU2HHZTlKMj2MDYybi14m7Wzr4C/gO6QalmQ0T/tMb5p8z8fRVtPxvAP2TmNxPRdyGlUxResuAzrvg8+wHzKwC8AgCu0d1rTR8sWbtLGLyS/pdlJ+UjvDtcQExwnuEZ8mppq+eRTntjLLcuF1G5gTvrRj3o+9DZDp8EgCTTtkWTe9zF8wg7+kZoJHtauSQR18tB7pwHYPt8dJYAtPVtX+TO9351ucDuerEOslcbteXObnaoH1rOhm3xYqHrCgDxeKyyWkgJJAmS0zOI8SiT/3+nYAkxmSg6yO072fVqA5BOHWna3ryhEJ/TJ6pmw38G4BDA1Yq/r644/wEADzDzm/X7N0ApzB/U1Ano/w87xz/FOf/JAD5Q8fnmcF23TReYOgnX17VXkq3BpJFzcx/zcpXmiwQyliubQcJYwbcoKGIQQwyUkiMXi+YLq3d8Jp9ryIF8MeHkQQawmTLWZlxscq7JGLFHctdKiW0wN+2jeztgQ+jnLjRNr9OmW6R5E8OhojCtVuCZtoLHMaLDKzon8h5ZVyV3ZtVu7EkrQ1gne0WVb/w1zPyvq07WlIlCMPNDRPQ+IvpIZv4jAM8B8Hb990IA/6f+/xP6lDcC+AdE9FqogLzbzPwgEf0sgG92AvM+E8BLa/y2SpgIeVXvvQZZflsD0VAXokhxkhcLwHIfnUA+1vlPaQDwbnbZLBliMlF9JJG3xFefnH9flH817JAvDhzvRy2ZA9JxscsxQAIUIZU7w5ffkdxl0FSBaEJtCbgYcDd5UQ+ytKE11TX88JnKe8zzOXg6Uxbb4XDjMtZ9gJNE3T9BQJO1rgA0iAHjQdv1/BZQilIFmZm/Zt3JNY75hwD+MxENAbwHwIugrNavJ6IvA/BnAL5QH/szAJ4L4N0AzvSxYOabRPSNAH5LH/evmfnmur6VwliBVktQPGjm5nXOV41066YioYL0xHBo+2UoFmI8UrmYZ/NsRS+kyv42YbNXaDcZxR3wQ737mfldYRK5EHArWNZyn7ocZNVAj70ruLzeqGbkzlAsdiB3crmymTUynqaWC7aF9mQFubtYMB46KuMg13nGmh6VoxVtOD6S0zOAJaLr18HTGeR0iuj6dYAIcjrrJ5XqpnDloAPuv5zN7b3cCVUroBbWRlcRUQLg3wJ4KTOz/ux3mPnZ1WcCzPy7AD6h4KvnFBzLAF5S0s5/AvCf1l2vFjxLpZhMIGfz9YJoBMQ9rmzx2JSTZYj7+jokYlX7HVApYYhUFPICmQVylwn9KR60DxZylSBPGVIWx7BIXwQUKXa1n+uOnr/KXCFt5Pq+yJ07h5GgfFBGG7BTBCjI3fmHSwmkdsVlijaFm2Y7UUaeIcCsLLOJUOnerkyAKbJrwp6B4kE7fjRLZfxaLdX6FrCXqPNk3qaP+zmdkxgoDpw7H/AtwFTzpzQR0k3dk+5kYKLUZ3OlHLMEL5YgITKWrK1XFtN9s5UFI5Epw9sKHrcpNlfyAAAgAElEQVTbTsR7OEEGbIimluCug9AawqSiAtHu5Q5ZXjBLthvULpFRgALV4vzDxLcMh8AgbjWfFm0KN+Wqs2TQZAJ5cmJzjNNwAD6dWo/pruSsECQA7iZzDEVRWqFzx3NcQDnqPJWVplK8EsCvEdHHA90aLHYFThKVGWLTCaMq28UGoEFsXWFiOFSTxWppJwoV8ZsvnLCL8rupstCRgPvpbtw2w+RxIWDpFSa90TmAtaKuVpny7zuRO31tm0mDZSdVvbwL7IzOEtAPTElyGg5BLeWuy82YSxE0nOPk5BTi8AoQp97TvYAx2iwWnQSvyuUqlHI/B6gjLQQAzPx6AH8LwA8AeHqfneoderBTPACaLHJGietpcTeVdeRiAdI7aMUvXMKkpZPTqTrW5LXUVqRdgaVTKKTNfSlYjEMU/QWDdt2vzQJTcF6fclcFEqRiFbRsmkIhO5U7fT/sprljC3KQu4sFs6Hj2Rzcwzy98fhjCXlyohRhHUAY330XcHQVEKSC9vZIiaSh2tjTZNJ6c2zPD9bjvUadJ/Pl5gUzvw3ApwH4R731aBtwF9u6FIsiLlTHA9vmWTXCE0Wg4SDlJZOw3KcMD3IXlh7z23Vu5lbRxrsqShCwXTjFLYxVq845FrsaH5pGtBdyB+Tmok7oTTWuE3B+YQtjzdYX0Vrbjo9Nx4heh+n6EcTBgVKUrx4Ct49b9bE3JFJRP8aj9m0ZY0FQjvcaVYVC/obz+sO8r09661HfcFyjKs1bw7yQfS4YUQQyFioTOBhFEEdXkTx201IsYCoa+VzdLcJE3jbOSlDeYC4Acp+sBwHtYYL0WArQMErTHNXBLhW11WrP5C7JBK522g9H7tRmPCjI5x5O/nExmQBnZ7vuEQBFKRQHB8BwACwWykJ7fAKMR8B0Cnl8vF8ZHgSpWISzqXrdErvIox7QDFWmh8/zXv+k854B/HgvPdoCDF2BTDB9nXRNWxjEJhgPIgbFMXg+VzmQpzOYXJZAWiI7LXQyQJuqPhv11SjGgkAiBtoqyKqxzH02lvOgKF8MZGgJZiNYR+72wJLplqbfudw596MPHnSQu4sHG7tS12Na1k4RnWJD+RQHByp7xXSms2sQMBlDPnYT4gn3AR1UrOsU+t7xaqUC7FrCeKTWbgD2YP67rKjKg/wi85qI3uq+P9fwMkWgziJQlou1bNC2HNByOgXFA5AgxUdOEuV+KnLr7sJFQ2kmDbnUwUt1Cz+UtGcsY9mP98h6ENAeOnWheb128fNl1Zy3TZR5MnYkd7nXPSyeGbkLi/PFAEv1TLn7+PqN5mkSQBypAiH33gCiCPL9D4Ke8aEQ05miNenCIfsCOZ0hunIAcfUQq0cea99glzJc1UaQ4Y1Rd5a/EFkrLPSix0kCXq7WBxm4Vs0eeUOcJBCTCSgeQIxHuuTmoQoSms1BBweZKHbzt0tLjzCZN1oi8wwcgbafB67W+YeWO6llrrbXRvP1dhI8xjKTSs0WCdmV3Hm52DMl2tuiSO7Cwnr+oWNXxCBuzUHuDHpcJcfHwGIJHsUqMP3xY+D6NfCjN1WV1o4DUNtADIequElLKzyArFGoCxkLctoLLqXWocpLK8GTddO26MWjVvL8TQarjkoHkUr3tlypADjdRzFQlAsSpIJydMDTTuBY9eSyRZo8tz2vDdd1vFe5MAM2Rqa8uwnUW3uSrnxp+PdbBkvOpFrc6UbNlzMjNx0ujhm5C0FEFwMuXaaHZ7qxXDIjvu9e1SdmYLkC374DfuxxxfXV696+gIYDiMkYvFy2XpMsz7/GnBKyyuwOVUF6P4nUcvx0Inqj+z0zf36fHesLGVoA1ADNWYOKXBJFtIoy18UmLg2WEFeugnUaN3H9CMnNW4DpaxyrYCHJANLUTsaavFUqguPuFpNxL24wWxrVTOjckt8csFsYWo7mIKfV9NZsOHfMQbYBvasl2FvIdiZ33rW73Di4creTuSWge7ic9ckYKLIi15QxFYydPU4Mh5BNAm415PGJ6s/JCpRI4PAK5O07Kuf4cAh5drZXFmREEbBaQd45aR1v41aqXMtD3ice9iVD1fbsW53X39Z3R7YFl57AkhHddYTk8dv+QcUn+ymnOl60eblUwW7Lla6a5yju2pqsrhll3aw7KlVJUaSs2sMheIMJMteW2VXrRdlOxsF9dCFg5E4uV2pjtahZ5GKXxStM1huvSAgn2J11laWS+Z5S4Bm5Sy3IYXE+99BjheKSJb/O+ClRojfaoOn4H3nnRBUGOTyAfN8H7FpCBxPQbA5iuZHy3QeSW7cQ33cveLGEPD5utTHlJFEbi4YUz00QNrmboypI71e32ZFtwVU6aaTzGTYtWGDaKovC35BiwQu1KzVKuyoPKiDPztTE4RQpMOfsTHm0xQr0pNvSBV40SfBqWR4kFXDukKkSKYQqWnAOYOTO0ol2HfTiBg33UGggK3dB9s49zCavapNZc0x3atElgejoispkcXIGcc/d4MdvqzzDOrXiPtHrxGSirN4dFDARpjjKYqHX9PL7v1dW9EuG0pmViF6x7uQ6x+wjKDbFNxjy9p38AKyq2tWD5dhvm7WFDYAKXIgHkItFKpTuomi4y1uG3RyQUGlvWi7S7m/wq5TtnPsZ0B56kTZ8Om5aarVPuatx7Vy1yB3JXeYerMumswEyche4jxcDjmIsj0/yc6lLZauaZ7m4vPqmyiINYmAyVmlMpRrD8uwM8s4JVo88qt7vifU4g9VKKbhtEEU2VVxQgPcXVRSL5xPRrOJ7AvDXOu5P7zAcXooiyNkc0ZUDkOTdJ8TX1AmjuAPakjNVi1TGHeO5VknE200zYnPAKk4bz+fdLNJ+HmRTalsHdAU30cWAXCwgxqONuYvbRC67SvrFjuQuX1CnMwXZzEG2xL2TYu+cWPsDyiGXKwgbc5N+bsqpr/UCGm66/3GdfOa5pkitv8ygwyvAtUPg+BTi6lUAUEpzJIC53Jt539QmoGtXW1uQ2VSe3YZsBZrUxqhSkP9ZjfN/rauObA16FywXC+vmEOMRkpNl5pjMYlgyiDeZGEphridIRckOh5p2sVBUkNUqpYe4rrJdURBMOqjpDDQZQx63LA/qWcY4AUjE6n4samY8aIKw6G8Xtsz0QqUynIyBxbK6mt4ePCM3mGYv5M6HDfLppi9qM6rlzgbp7cHvDNgYxjosBtp74z1Plgwq+LwIcpnPd7+pBVRMxuDTM9C1Q2VNFQI0GoLnC0WzkBJy38aeqXLbtuCK5iDXkq2wTu0MVRzkV2+zI9sExQM1IayWwEy7evyiBEWuzNoXaLGwE4FE1s3FC51WhhgUeRMS72CH7aSYI5bK8tDWTUQCJNLfYhfmuunAAvYeYjgEtOVISM7LnY89WBgK83CblI87kLverMe2yVTu7DWC9encIzOHFoyb1EtX/qxJkDUuZT4vyGxR0kBqWJEM6LzMNF+Abx8DkYC8c4LoriPIk9PSvu4EZkOcJKDDK5APfbB9m2ueScDucfmInc5Cx0kCGg7qVcoq4GYV7abVoRsodMYqNZ+DpVSuHB2QR4KUpcjJ32yvtaMgBssllayCCFsqsdZS58CkBcsEJgacT7DU3pFUZrhEfjLYMffcKAWZ8V3CxdxSh3L/u5YNNx1fH0GAAduHKcxDcZzfZCG1MtdpxwfVzVXsK+WzucrOJATo3hug0QjRjbsg75ykNQH2KEiPogji+hHkozdby4QYxMo7bNOYboNmEdAUl+6ukSDwaql2wSSUy8R387oBQWuCFoq+32TBUhkrBrYgAWn3ixinEbNFqdRynORtwOTUjKJUaW/ZB3ezQVFkAynF4ZVW7QbsEUygm1GWa7gXd+09sGnd/M3bDuWu9H1bkAANhxm5CxvTCwA389LBJF8MBmr+XVeVsUxeN0nxSYKARKp17uQUOD0DBjFw/RrEtUNgOICczvZKQcYgBuLYrtNtYO/1FuYQY2ALaI61T4eI/vw2OrItuLl2xUClJysc7A7f0I3sLvq+EXxXrfOahEiD0uJYKfPLFcTBQWrVKbreDga/nSwld1Ju2ipCDhcbgArUAIKAXwAYpVIMh4DxjFTAlnjuYhHZtA03g0XfCmrN/tT6bANknkck0ipmQfbON/QYZsnAlYPMpidTGXbdc+5SmSMBujKBnM1VDMtjN5Vl9uQMPJtbqkXbghxdgqczgBl03z31reZlbTnz31aMAL7nKaAW6tyt7yWi3ySiryKi6733qG/oXZutRLdYFn7vvk+rftUbZKW7y6q8pSwhZ3OrGMrpVO1WtaXNKulFCvYuCxZ0FRxkJmptrWNTQTCpYckPODcwC56cewlyilJPuXJk5LLNONjg3Izsu/K2I+qB7U8PSmtO7vahvHZAa5g83mI4BN+6naMLWaxx9ZcFg4rJpH5nXMPTeKxy/t+8BXH9SBmIFgvwagUxVjUKqG06tS5BpDI2rVbtC2O51IptyFfY5G6EtU+GmT8NwBcDeAqAtxDRjxDRZ/Tes57guhtYcpYorz7M/oda1F0Lp6kI1hgONcG/BqCjenXicONe4iSBnM5sPy0f2fShgE+2DVA8sPeiDzcsJ4lyw8/naYGGgPMN/QzlYpFah93vvPFr5a4g9d8m167cuFa16S7qRbK/Rbnrm/Lgyh0HubsYMN6PSKisQ0VyUKdISJKkXoW2IFVJj6czRM/4MFWA4+7rmsIwBIiA5aq88t+2wRI0GIBPp5APPdJJUDqvllvJEJPxwgV5boRaMzszvwvA1wH4WgB/BcB3E9E7iehv9Nm5PsCSwZKVm5elSi/jC2FRhO9olFo4db7IjZKFa8HI9StJkBwfK6VYZ60wgXpiPIKczSHnMzvYTR8y/fUrJnUNx4pnop7TH9BS8BwFxiohkpGcnqn73PVvChPF1mE9IWb8+IttidxZatE6j8UaJbfUXVtRhMRW83JSu+1S7gppHh1eNyN3Vw5SeknAuYWJ6cBqpegMZcGxa55zWZaLxgV/9Dny1h0kp2eQf/KAUoRnc6wefEhZZ5lVSedpVSmG7YKnU0CQyv3fllJovDPAduQryPBGqMNB/lgi+g4A7wDw6QA+j5k/Wr/+jp771w/MgkhC5VtkJ5WTv9iwhBiNldJqrKb6fxkygz/zhVOxyFzP+c6lfgCwi7Gcze0CbCPqfZevc07diOSN4VnjWl9P31Nbmc/seCNhi0nsOlgruJm7heH/A1grd2I8yo79KpQ8p1K5WwdHZvdB7rYi11rusqnedoQgd63Bkm35cBoMslbgBvfXzsveORtZeXVWJjGIVU50ZoDZjjsajZQy2nWQXovxZKgqNIhbr0d2ox3oFXuNOk/n3wP4HQAfx8wvYebfAQBm/gCUVflcIqOIaleiTenk8A4pHqhAMZaq+td4BHHtEJGxrhS1XWGpMhapIsE3CoDNM+koBcbdzKtl2ndnwXQtWJncrT1ZXtlZPDOBHhtez70n1q2+WlW7xreJMMl0A4feJF258xZDV+5M6XUxmUBcvVq+OOm2Cr+qkLt1YzYn5zuUuxxcq3Lba2oLuZG75OQktZ7vCkHu2sOdQ+UaD0TVGDKGJd/TM59v2C0JGo3U+XGM5PHbdu3j+Ry8WOxPkRq9FisKUvvUiq4nKmSK2V/UmVGfC+BHmHkKAEQkiOgAAJj5NX12rg/Y/L2rpVp8p9Os0ue4S42ixvO5SkezWChKhmRgOCgf2FRSZcvhAWWUSv2Z4omZUqBZ16bhbJZa0Ux/3bbc63awePptyeVKKeyriiqENWHb8FJq0XC4V5HMAe2Qoyfoz8zYdqkERu7kYgEk0uYtr9owNZY7ry+123TarpS7tvCVF6+v/sai3aXSeYWGQ4iDg2DBvSAwc7W8fSc7nhs838JsTsBmgXQkrEzL6VR9pAMJEceAngvEZNy87So03HDZOYklaDiAqaDXVuaEKZK0QZ+aIijgm6OOdPwCADdM9UB/di7hWpLKLD42w4Xh+0pWCcIXC8j5DPL4GHw6Lb6Au2AWfW12ob7Vx/x3Ji93QrK7TZcDaS+pLHBWyUh/SPq/CyH0F2cnqnkd7WRdu64QC5NbOY6V9XAfIpmDotAaGZ6uRzfKBXs6cmeqd8nZHPJ2SUnzNc+nVO7Wwdnw+cp1LbnrAus2nS4/ucU4tXOiljvzWRj75xyOrNl0b/rzppvF4vY3pBsIAlYriNFY0Sq00mjKTINlPstUWzQcy246NjmdqewuUivLLZAxFPThcQroBHWeypiZT8wb/fqgvy71DNc1ytIW5HDdUEUKKExQnrGelqV5qTPBuEqxERA/o4VTp90EFZZFEOeq67nKalfuV/byQVfRRTZYqK2CpM8Tw6FqezxSbriwCz73KKwK6cudp4BCSkT33rCfyTK3axUVx5MBN+huHaqCaWrJXVu4v6ugTVvyvSOOvit3vFjm0/FtG0FxaA0SpDyQq2U+l75voCmIizEwPGYfbWgQcrFQCrEQYCkhjq4CiyV4tdIlrLtVkBvJifFk6XXJ0B/l6Vk3hUL8NTVg71Bn9jklomebN0T08QBKzKfnA6bspphMVN5Pk0LNtVS6EerDIeTxCcSHPAnx3XdBHB5a61EOJKx7qODCStkdxFmqhImQd3f2puLfcqUU40hkJyxvgTeBbK7SkcvfXNTXmrBKhRvg6OZJ1Z9bJaGtgiBIVS5KEtjgjVod7WlBDVzI9jCbqniQKRRCo5H93j2WRiPIO8fAlQPE995AfO+N8qI0rvJbeOlU7txrrLPeZPj+3rWADeWuAaxV1x9/Lm3ErcrVYpza3xpF1pMVHR7W7GiQu72FHhdiMslueMyc7Rdpcr7P0G5cZc45tlEeZLdbUaQCcadTVRzk7Azy5BRypvjHMDFAHaKJocUPupVaV+DFsrVlm+JBsXEpYK9QZ1b7xwB+jIh+jYh+DcDrAPyDuhcgooiI3kpEP6XfP42I3kxE7yKi1xHRUH8+0u/frb9/qtPGS/Xnf0REn9XkB5bBLLIZS7DL8TW8I10TnpcrII6Au6+Djq4qJdkf3GbHuViUW6icHWmuSphLNXDSyFnKh8kLWxRJHEU2FZ2hYaytQtZw8clZ1h23dYY3vIE1yz1fLnUids1RQx1LguOqb4UmC32wbjWDM24zzzOROUuttSovV+BHbwJH14CrhxBH10rzuFZGhlfJ3Rq4Aam+ErqR3DVApXKcPbATq5aKzeD0Xq5zJXcld05bnR0XoKDHvlFILcx49nn0JcgYhZzj5Mnpxl0jh4ur1l7tQdTVY3N1Ctqg4QbSr6AZXTnIft6mKx1Unw3oH2tnGmb+LQAfBeArAXwVgI9m5t9ucI3/FSpFnMG3APgOZn4mgMcBfJn+/MsAPM7MHw6VPu5bAICIngXgBQD+HIDPBvAfiaj9tosEeLFQViWtiMr5LF1gHesSL5YQVw4g3/8gcPMW+M6JsrD4lb781wVCZPMvc0HREEqD+2yu5UGsFq1EV5hzS/Q6FgD1uUgnwK54xxp+7XibbYOyWSwau8ScCdotvSkOD5VlYbEAjWrmQaaS4MgmKFJGyq7dFX3lksAGyJqgPCN3i4XKaOG6eV25OzkFP/IY+NGbWQ5lGZrK3To5MR4Tb7HehtzpC+X743fRLNpNlEx/ky1IKSZa7sRwqMrr1mirldwVzZdB7jqDWTPkbK5SlLnZggzIS2NYcP/lclUse1EBPWN9p1Sbs7kNvlVBoQQaxIrvy9Jy4Ru3X4DGaRjd+8BSpaMjkaE/bt4ZUu04wem9wZ8XgtzURt079YkAPhbAXwDwRUT0JXVOIqInA/ifAHy/fk9Q+ZPfoA95NYDn69fP0++hv3+OPv55AF7LzHNmfi+AdwP4pJr9zsO4QY2wRJHKSmG/5syglYuFstxePYSczZHcugV5fIzk9Cxznjk+M9GUwExQZtE2biSfcpE5ntN0WLkiHRrJ6ZmK8ve5kGXC15Qn7G0IMkqtG1C4zoJWxHdLT1afS6krKgmAufD35s7bNEjJXxA0faRqo5M5tu/8txcFzuaKHDd+bnPlyt2RSusmj48hT04gb98pb3sNXaJM7ur0O1WGUxk1ykJjuWsClsWxBx4dBch7eHLw5a5EXqzcRSItkFTRv43lzu2LebuugEKQu+ZgmRpzPI9Arhqru4n05lxT/tmHsfo2AolsIKhQ8zyiSCnKmmKVy5DUF/xxVEDZUrTMMWg46MAQo4Nh+46tqVrDAtZibYZvInoNgGcA+F0AZlQwgB+q0f53AvgaAFf1+xsAbjGz2RY+AOB+/fp+AO8DAGZeEdFtffz9AN7ktOme4/bzxQBeDADjNTGESsnUbzQfWX+RTva+NWM6U6Wg5/OU8uAKietyMlylAhmSiwWioyOQ1C7ZBYMiWEusVR5IAEy2LRNZrgQ2a0Vz+2FKVBtF2gTSFQpildAU3QPnvaVWmEpj/nF1qB2eJcilkiQnCcR4pNIAnZzWr6DWZCIo6qNvKaxhXeSkpK1Lgiayp+6noeY43EdX7lxF7nQKceNuyMduFmZwyfWljtytVtrljIzyW/isXZ4yL7Ntu/Kgq16atni1LOcPNwEV5FwtkrGieavot3j9du8XJwmSk1Mrd8Qx+Oyssm+5tuugqJ9OW7WUhiB3teWO4oHKElGQIjGz6QMqx5C15nrHJKdnprFmP0AQKBooBTsSqo+HVwApIY6uQd6+YwtFdYFNlFqbpSmKlDfF1xVaIvWqtW6q7gWDstwAdUrgfAKAZzFzo60OEX0ugIeZ+beJ6K+ajwsO5TXfVZ2TfsD8CgCvAIBrdHd5X/WCw5IhJgPLf7T8XkSpBdRQGOIB5PExxBPvA+YLyMdvlQcKaQt11STPyyVICLWo6h28cbeYKGPjdoKelOR0Vu7acRcXx9WayeFYojiUd7LEjWsvSWApMtZtTr9cL4TOvSqDnM1tYBWTQLo/6xjeRqCw8EmZNatA6bhsqC17hUqRKeVMWbmDWtiT23cQ3XsD4t57wCenkKdneRqPcw7LcoXJyp3ZdGrrrHreFdQgo4z5cOROLhbZ/OlOeey2yP1ed8y5nqY6Mu7NUUXziZE7kNqYoyMFpRBFm2T3syB3pWgmdxHE4RXwfGFjR8y9VvO4OtSugUkCuxZqlGWVEMOhCv5ronwZT+5kDJ7NkTx+W9MdB8BiCZpMIACw4TeXGa+aoKk11ZEvlgxhipq03fQCStF2x3yfiqv/u4OSXBt1FOQ/BPBEAA82bPsvAfh8InougDGAa1AW5etEFGsr8pMBfEAf/wCApwB4gIhiAEcAbjqfG7jnNIde7Ew0qlXSPCsmgJx1Inn/g6nyS05lHX+higfgkvRIFEW2vrxxnbJktUt2FAOwqkNvFnAxjCDnWknWv8P9Taa/aZ+WWqnEeotuHXgCZbICmGpo7nFK6Y1Kd+yuhdymqYoikEitQuZ3yOUKJFkFNRQpRiX9q4Nc7l23nXVt11GgAzKwpcSN10GPy6JF12684gFWDz6kot1Nmil/gtevxWhcnJZMK61ZuVNynBu/Bf3IFVbwlDM1ngfFctcWDdowGULK4gByclewYcnJXdkGtsVvLFTkXXkyVv2SdH5tr38pEcfg6UytefreueuP9TSa1J2xKEzrFj3xCVh94KHMZ5nx5spHlSJGQlGTZspIJCZjVcHx9rH20krI6QzRXUeg247HtKWSV7qJ9Nty10z9OhOM2FbJ1BQmGF96z+NYPVu9ASIBXgW5qYM6WtM9AN5ORD9LRG80f+tOYuaXMvOTmfmpUEF2v8TMXwzglwH8TX3YCwH8hH79Rv0e+vtf0lbrNwJ4gc5y8TQAzwTwmzV/X3n//FLJmS+zCyCvlipfslZkebXMR7K6i6WgTM5kC30tMRnbhUca2oRWBlxahBnMbrlX6QYt6DYzgsz5jACd7Bg9jmfGLe3dw3WurMy9K3H7mv+2mmGRFaulFamqEqK1/lW17R7nfhawHkVy5yAN5FPcXpP/2FTAzDXnyl1RexVyV4XSucHrq+lDTu7aYl0bRQt72aFFcpe5VF7uSn9HC+t4Hblb6w4PclcbLFkbgxji2qHKHAGk6Uide5kJ4PPvqSDwnePcmCiqjlmjU1b+TKArSECencEtPMLTWc6K3fhazjWbwuYF10q86zFtBZbKm9WFNXrtdSj9729gAipRx4L8so6v+bUAXktE3wTgrQBepT9/FYDXENG7oSzHLwAAZn4bEb0ewNuh9lsvYW7B2DEKXjzIWilYAjQAkGaxMNZiiqI0qtvh3posDrZd466iAsukuQYArJSL11ivDF/RThhaIQeQ3cVby0r2t2QukSSg2FhhSlzDG922tGIYr0zJ3uLE8aYfVfD525auYe6/c0wmr2wDhaAWijYQTVxwdT4LUHDGrwk0zaRlK3i2PJ9DjEcqAl/EpXxElmzpSKXjpEjudKBeZfaVGguJbasPuVvXlvNb1/F36/AwXeMBRTX70AXayE6Qu2K4YzeKVJBrrJd9IiAitapqz461Khv5dMdTkiCZzfNW5aMjJEZxLvBKqAaL50oaqYI0rEthA1BUkNMz5T11U6Z6a+0mWLs5y3yUBqC72aVyXqUNYD00Lq2zwtq+8fh211JKqTSdGM0uAdYqyMz8q0T0YQCeycy/QEQHABqlWWPmXwHwK/r1e1CQhYKZZwC+sOT8lwN4eZNrlndGOm7eYepK0t/Zwe8INkVDyOUK0eEVEAYAs7VoWouua5lJUqXXX1hM2VyrhDsVjni1TJVQJ52VGKelX31+dLZxYRf+zGTSyW3LBiZaDrLJqlHwWwtRQV1wU+zZik/GPV6l/GyKOhboBnzqgGpkqiW6G9L8gXYMyOUKIoqUC1YICBLFNArWSmmRxdO4SAvlTo/htotQz3K37trOCfWOK7mWGDpVBu297Fg7rnOfg9x1A07jPFS6TJURRn3HlgtLQnseh0PwYmHHnbs5ooPj14wAACAASURBVOEw3YS69z1ao7hWjUm9aYUgde3lSlEZyDHIOPQKTozCWtFuFyCR3SgKgjw7s/dInlYEr5a05/aXokhZ8u06Xy5jxii1yW+w/0kr4NzS8n3JsHYWJ6K/B5V27fv0R/cD+K99dqpXUDZLAV2ZpEUJvKAVP0ODnM5UBLwbyVrQvkluXra4WTeNy8M0LmXt9rKvHSXO0i5cJaCAxmGOz/x1AJthQ/+GDAWkLorcot4z8Y/LpLXb1oLYhONYZjUJyMBaSYqsuwVKnnnmcjZXcjebK9kqkzvv/NwhJXKXoy3lO158LYdu1KfcrUWd8VY1Z/jH2ZdcXtq7bwS56ww2GG++AN17I7XGetQIuVzZdHCW2pZJgVpiUCiT66JjDfSzMrmVXQqdKRJFTo0CABkv60ay1XBDJYZD0GikFNkoUpV3JYNl86I8xVV3s/UMcn11/28CrqArhY1lLdS5+y+BCri7AwDM/C4A9/XZqV7hWkdYggbZnIa5lDeALffMqyXkdKr+jOunwC1DRfxjc3nDLzZKuTNJWcux2x+doidHNyjqr8sz6gFuSiCj0OfSvNVvLNe2+9p1aQGwlJheUMaxDOgW5p7qBboODcfkLJbTKeR8BjmbFx5rebNlY99sMA2lwlUOqp51EQXH/Ab9md3A9SF3RRZx//smbVWdw9JuFgp51QHnEkIXuODFAvJwlNkg0sFBZnNXZRm1WZc80MFks7HPMi3/TsKWn1dW2gEoTh3cOflyKRddoGjTTiItKU0EuqKq+/F8nvK4a4DiQeo5M58JUhkxgNx39hhfR6i8SMm98Oaussw1AcWoM8LmzGy3dzrDRM/ZrfsFCbKDlk/PMu4ka810Fj+7SPkCWgCWrIpcVCwquTzK3iKYsXA7lI8MZ9P0zxMuq8R2PIGYicvngGboD/UayqSfsyigW/hVBXtPqh6wNWTK1pbAlJq1Aa9l1CLoid8d+0XtGUuaJ3e1C4akDeVk1o7Nrhducz0fNSzmm14rl84xLKjnGmQoSkQQDzycjhdB1vjieiwzY9lBhnrowhQKaTrujQFqsVDp3QDQwUHWQGLWG+Nl9cdik2s2kRNS1EtDg8BqBV4ubeVdrrPm6bWuKP+0XK7yBcK2heBpqY06d+pXiehfAJgQ0WcA+DEAP9lvt3qEQ18gQWmSc+QXUFfRlIsFxGQMMZnYSPmyQLwMDaPo+q6gO27aTA5jQcpirflg1nLrk/n9xdr0v+2iWbSjHcS5LAFlVf0qUdA3267H01pr9SrCrieAYH1ei1w6xTKldrEADYcQ41EmC0VBgzmXcAZ6wSuSu0YoU0y3TatYZ1neBOaeOHJXqhRVnL8zBLnLgwTArPj7Vw4g75xUykg2swRl5I3ivKIHAJjPm9ErMofotY1ZKeyrlSpUY6yr3jqaCZBr6jGtOK7IM0ujEcTVQ8B4dqczFeDorq8Vllsbc7HKK9MmGLK0CIqZy7qYU4roGruW1XOCOnfpnwN4BMAfAPj7AH4GwNf12ak+4XKYaDJRH/p8V4eTnOHdCgEaDtVfRYoorsqt6rmZM9f10rAUVT0qPN8NqOnIsuQrDiw55awBGUUjVxhljUu4UMl3OM2ZxX+T3xMWyv2Ex9PN5Tb1D9deHjmbg+LYBshUtl/FhTTy4Vl+a6UUq3Jh+t9tU0nuuj1f7prwNoPc7SWsFfbqYbpJ1JQGRJGyimqPjp+yLePNdDyrmfarNlE1FDG7tiQJ5HQKxNpKqyteGqOP7Yvx8lJ1qsgmKPQiMSulWAcM8nIFJLKex9TZZJj0lG69BQA2OL9o01EnBWUtcJrmLTM3um0HZbkUdbJYSACv1H8XAlagdZJyG6WrU66oRS9bZYgEITk5qebC6oGWZrAocAexW71L5igT5pr2FF29SGWMKKckbANlNIeynNA5VAminWTdLBm+2zq4ei8EihTZIo4vUs+KKfKRy+XpHG8yq5Qq3E4O1ZzcVY1NTz4zcBXvXSmIHV7bT+3VOsNHwG5hnpuU4Ju3lOI5Sy2+qigHW3kwvP+iQHS5WKSKpEvzm85y4yZ3/cLPUyWQdJU6Gg5hsmv47Zk1M6dQdqRI5j4yirBe3yhS1W5tgayya7ueGH1MLriQlF4hF4u06mZROzV/W1UqxhxlpmgOCyjEWgWZiN4LFJZ2fnovPeoZptoUCYKcz3TuUqfgxWqp3tsTVGoZMR4BpkgIULyg+lbcEp6tH4BmznNJ+X7BgVzOWAc2DUyHi7U/OaXZKwBeZctpN9rFl0wEmZzSbpt9uJIDdoMiq0XFOOXVEuLgAJjP0/zjlc1ztZLsyV9GOa7oh22z6Ddwt3K3ETq8pm/VD7z/cw4SoNEIEALJrVs26JWiCIiEruw6rTV2fXqDQSkfd51cmepuEVQwXBQBlPKi3dShbpW/TdeGWkqkAzEZKyuyEzPk5kQuhaMQp3NS6o02c5lNm9fHnOF6Yt3NvX+/wua3EnVCMT/BeT2GylV8dz/d2QJYgoRK25IpzpE4Qui4moxA8mIBcXgIk5qFFwtr1fLbNzvxQpBTPcdTEiw32XEduVkjyly5pjxzzirXApnci7rtwmp5TVyxvoA67zPJ5gvaahwoFFzD+wtjNYoHaoy5fD1vMuf5HGIyUW5XXbBHnp3lx4MvCz7K5K6OC7iOC7nPRW6b8OWuoNxwwPmB4fdSrOJHaDIBlipGRoxH4NncCQR3CmXBM9TkG86NFavQlnlbPFhF0RiGliuQLg5CwyHkbK6stTpjVCbnvq8k15CTqs0eDQe2P4Cam5KTU3WP3IwuppBKVWEhpPfOrU6Z8cxMJpCnZ5nUk5kUs20r7JUpxb5RIKx9lVg78zHzY87f+5n5OwF8+hb61g8omwC8KK+qzQyhPxfjkVWS1QcEGpRQLRx+VJmV2aSbyuQ05pIAI9dd4w76ItdwAcdyUxRVOPODNsxnjYSsRHB5uUzvW9E5TQU5CP7+ooArn6PTkFBeG0BZuFinFCxLoUgl2VGca4hBXCh3nWyk+lAi6/arLwW2o7kkYHcwHH5TiANRalmkKAJpGTOy4FYt9WNLSpU2x8vZZMya+d5UtgRLVVHPcJJ9o4xel3spz+wF0hmqibvecZKk8UU1udVuOlQfJhDfZOBpg7XnF+kLAWtRh2LxbOetgLIoX+2tR9sCUWbHWAiWoHgMSFY72dnc8pbV1+WD0vCMCyvg+Fbmgp24mRwsHcO/VoXyDaDUldQIrhvNWrQLrMpNhc5TkklHL6s2vZ35JlY0/5w2lrjgguoH7JVj9iwbltITDyAXC+VdgI7+Lnke6ygWLs+yq99goJSJHsZKnxbqNddtnOKtS1kJctcNjMfUrHez1NgBIpDdBKWcX4pSC7JLN8zIVglVrhAlz9Jwmq2V1Ulpav87ltqMlbUqLmADFMbWrJapB6Viva5CqmBnNxt0/ZpKB+t4jdugshy8O0+Z44Js1UIdisW3Oa9XAP4EwN/qpTdbAksGJQX8Q2MhdXauRokWh4cQmNrKP4W7SKM0Js57D+kkwJlzAFh3kl85zvKeqnjPDmewNJCpCYoUTIf6UXcXXe9SDBpGgFylVos27ddxu1V93/HkG+DAubeFk7pzv+VsjujoGoQgWyCkNILcjv/i52pKS+fkrq4CWsdd3DUPeVdKonGxN7VqddnXIHfdgVTBCzmbIzq8AsBYg7VX1JVHyaDxCDSfAzTIKKi29LNn9FHc3Iq5usTqbIv2SAbFwqY8I6G/Wy0BeLznBpSKJiikbBkruksFMXQIWTeTRQG9AQCmM9DRNeDsrH85dz21IaagEepksfhr2+jI1mAEU7uDaDBKq3PpCUAusgKhXCtLiBt3g86mKiJ4tVKuX69t17KayTrhgHTUakZ4vB2qyp6RBt/lgvTKBMq3zG2IjGvJsRL7WT8KldlNlNMya77PmaqLqvOqFO9gueoXRV4Jv2KUO6EvFhDXj5TcEYGnM502qeSZVshFody1gT9WulSMm2BTGanT5qbtBjnaH0RpfmM6mADHx/YrunoIPjmFSxckbQgRAwLiVEku8ygYuUI0KJ9vS+Z2a4jS2SHUxwwaxCqI3km5Wmm0qDPeKr4Xw6HNFmX6JQb5VKeZDB914K6N7hx1cAB+9LHsMZvIS93z/H6sOyfIL4B6FIt/WvU9M397d93ZElimfGJnUTaWW5vuDWrxptEIcjqDuO9eVfFHux/le/4k2651SxoXlnJdZS/NiA7HSshMdL5VqrOCZCYmS/h3XFC+UDUqS1nnFrnBEM4CXBpIsInyal5bF1Y2k0VrAa2jaKxTcsoUL/e8MJk0R4H3hSKkQbKSbcEAns+VSxIA3X0d/PCjSE6W3ulmMStIrwgtd1dGYClzcre2nxXHdC13GdQdX+4Y7YJO5J+/iXLcFkHuOgMvlpDGYyo9Y4ZZ83SVVIoHYG2QkcuVVRwBb7534GabaPI88vxiLfPa8ETxoJxi0THS1KzGik2WG52peMdpTua1hqg1Hl8ajUCuR7op6q5v5j872afWyU6QKwD1CoV8AoCvBHC//vsKAM+C4iGfSy6yzedLIi1QgVQATbCPEWBx/UjRHx5+BHx8ApyeqiTrlr8Fe37GPVk2maxUwvGcu8M73rbn9MUG65Uokn4y8jbIFSap+u++biJc2o3lWjly7W6KsrbYqcDkW8rMf/1XGYgZ0Alcrr1ROMVwCHHXdcVBvn0HfHwCvn2s5C4u2NcXjUf3a7O4JnIzC1DZYue035XcFSqpdY/fxqZy3flNZdifQ8rOc+Wuq3t9CWC4tBQPVDYYYwSKY/DZ1H7uGkAoilSQ2iCVNTJl3wuQeS4F823BCek8jHRd48UiTT3nrHO5vPhl169AaUYOIM0g5bVp0uKZ68rFov7cXybHLNV8ZrymVZ7Tde3blxUZOvTzNskBgvJbH3U4yPcAeDYzHwMAEb0MwI8x85f32bHeQMIG0FEUgXSNej47Uxxkkwidl1Yo+fgE4kOehOSBD9jUbuLk1O4ujbu3MA2Nf/lBnEbCFliBfZqFe4wqFpJyk+1kZFxVeodYmre1wT2q5a7yLdmcT1dT1r474ZlURO773C53Uxdv2XkF1v308/R6GU5rmUIdJpzGSANd03toxrcNtjs+gXjykyDf934kj98GAESrlbIC+2BT/IMLx2BG7lQHshvNddaUEoWsd7mra+Vucs11x3dhmV1n8S7yIpWdG+Ruc5BQvGNmgAg4mEAcXYO8cwIMYtC9N8APPQysVogOr6SpSwuUSZYMcTDK5+6NBHiRgODN3emJhWMqrV6X0uvkYgExGltvUtHvKXrunXBrnTXBrYJnvnM9uLUDWJ1NXYaqOBhg9cGHM2t4ri+bemWL+mDmP7ft4IFZizrb8A8F4BYMXwB4ai+92QKMK8ksqHw6tfQFlVCd0mA9MonUZ0juuQYxGUOMRxCTsSp/604iJGwAn5v/MAedfxIkslX5vAnFTbdj/lfuoo1CV1LtrhFKhDWTxscRMtfSXWkBKmpfK/fs7MxtoKG5ThOUTThlv8fvl69UFylHzoYkc82A2lCBOYOsdcOh9MiZolYkdx2CnvFUiMkY0bWrSE7PcimZMm7DMmjKhi93KaVq4x+i/vUld+7/EmSscOuwRrlsZaFts+AWyZ7fV/9/kLu1IEGQmrcPZvDDjyqOcZIoq7Fk0EBTCMYjJQ9m3ZvNM0ogRZGiOxWVRhYEEk4KNvdZ1bD4ZlKdsdRFQ9LxZNZVfXL+h9YYd2vzmXttZNK9GiOWUYzryJrbjumj+T3zBcRkUv2bylC1mSw6PIpSKqnrPQ1YizoW5NcA+E0i+r8AMIAvAPBDvfaqb7i7QRErygMAun4EPPoY6GCC5Oat1PUPQDx0E8lHPxUcCYhFgujd74M8PcsGMGgSPw3iTDnP3OWfeB/EBx8Bz+cqINAKYFZYMhk13O9d6GuIyUTVsneikv3fXHuXWmDhsUVVAIcnahTNGGBTc95YkQt/utNkqmCa3W0uGGQT5dieX/GbUaGEG6XfncBJwHJb17mQw668Gs4zMvdaaAsXjYZIbt5SY0kvmNGDj2HxjCcguvbhWI1jDN/xPsjbx7lmxXAICFKxBUXeAZaFcpcJMl1nRS74LWI8qpa7JijwyABG8S33zGQy7jT5HQUKaK7QSgMLdi1eZtn57m/VClzud3NFWskgd8UwxoDhEPLkBNH1645VlIBYqBz0pgQ1oCzCUtqxnTZFEFevIrl9J3sNTRek9MC8klwE1/NpNq0klJHKNOXykE2bmz5/EqVjtKhUthjEahOhc7CbfgpdzKQWdH8z45alKs89HinKGLC28MjG45ulep5zwyM3Cn8oAFQHa+8QM78cwIsAPA7gFoAXMfM3992x3uBYDk0SdTmbW8E0O2tVlGAAMAOCkDz4EMR0ieW1IZJJDDq8kkuBA5aKszUcILrrSFXey12egdMz8GqV8r0KLFj+zt1atN1jHYGhOAZNJhCjcX7g+wteHSur374bTey1LRcLOwFU0UvK+kNxDBrEWe53oZKwBr4FquC6ZdZCa8mMB2qTEw/U5OxbREz//X6FxbkenPtkCwQIVV4WxpKlPTA0iCEfvYnhH38Qq4MB5FAAd1/PLKCqSRX1TqMRxNE1iCsHBZctkbt1i/ia35KROx9lC3kDDwvFg1rnmKIGldbwOl4eX7mpgzLLbx1ombScV5f3GuSuE4jJRGVekgx5fAx5cqq+SCSSG4dAIoHhALxY6kI8lHpUnXlXLldAHOWNFxt4YWx8j/HqmPif8Qji8Ap4uYKYjO3YKKTdZRvMvi8Zg+s2menp+nqrldpIsFT87eGg8PxCGO8q0vXFGgXuvm7bLTUGbarAuvLt9CGTh3kTy/UlRB0LMgAcALjDzD9ARPcS0dOY+b19dqwv2FyOxmXjuEihLVPy8VtKcPWkDUGQtxPIt78Lk4dvAKsEPJ9nLTDaysqLBXg2V1Yx8gLB9PGrhx6252Vqu2vLl2udNelm5DL9b6/p/q7FUk1U4xGE/j2FhVCqLEj+MY5Fy24A9A7ctVaJ4TCTn3adJcnyTE3arSRJU+2VoFTp9ibMXBlSv51MFo7s5OCm9nGtFrm81sZqP4jTyV1XRAoLdj24Vk8+nUIuFhn/CMUDiIMDyONjJB98BCOdH7xsQleUp5WyylDxYl0pdxs+t9py517D90CUKOmZDBlVVm69yaAoKs8TjfxGvHawYo37s07uqmDnYhKAEyyVS/sX5K45WMIUCRF6EwmzSZQJogdvQkI/v0io76UEhABWq5xhgs+m+UssV1rRpcpMS/l+DWxqVQAQBwdqoxxPlCI6iIGFzl1u1p46GRhM+0Wo6Je/bvFqqYL4jeFmPgf0BsK3CJd3g/U6nqVLsU5bWamguutalVe0DLZ/7MhIlC0fH+SmEnXSvH0DVCaLjwTwAwAGAH4YwF/qt2v9wV1wXC4iLxZqgjY8yOlUBQwMYoh77wFPp+DTM6XQ+TmQnR0beKkV6CKOKyE6uqa4XJMx5O07epc8TKsHGeVB0wCkdhtLHeFblMdVznVwxXSa2bWaZO+FtAdfEc7dKKcynyNURrkweZozynEUKQv8dFbcpv59psymihJmxS+9c5xXHvy+lvTRcr8134pXa9zmzkRpLMfE6W8ppV/oz8Qghlyu1LmjEQj6fOPiDxNPOQo2aWI4hJxOoTJaqK/kzQXiJz0BWC4hT89AUYSVsX55MJtdqeWz6JrRXUfKtTkaQR4fW7mTy9XGC4Yrd3YsOXKX+81u+xXX8uXOT3mV68dsjujKAQSJtE8eMl6peKCKO7CX1aNqQ13Qx0K5WwdHjiiKIMYjJM5zM/cwF/AY5K4xVHzHMs2+MJ+nVuH5QnltBFnrsZxOISYT8GyuKQDZ8ZoY+fOVNymVpfrsDM4X9r8f1GYoFe66khwfq3ngEZUfWE5nNouEHWtCZhVw91pNlWbXI1EQdGdjk4ZDkN4EJKdnaWaLGmPNjGMzbk0/6MZd4MceL23DpJrNBQvWvKbZLNuMIPr3mntnK/2GqnqVqGNf/wIAnw/gFACY+QM4p+ndLFzl2OzodBADTSbKtRMPlHBovhHfOQZdPwLddw/EjbvzLlUzyCIBcXCgXK++y9Mov9ptwyenmsoxTGkKcA9PlTSfWkGCbGJ1Y8U1blZjxTJ/OdpDmau1YDfrpv2JDq8guusov9g7/xUXk3OWB/d3uO4dmkzU/dXKv7lWo12yUdy9qONSS50HMZkot72ZEN2+m4mw4FwzfuTZWWGaoIB6oIGi2IjDw3R86HsuH78FCAFx7w3QE+61lcAyYMWzo5EKoC0aeyxZW6NUxhord35EftO+Gy8TpcqmK3f5E2pQLAAb9EfxwLqaq0+QmYWwqJ/unxiP1NxWhw61xv2bk7uaIEGg4SC1brpzg/5NQe7awRhYjKJnAvMAKNrFrdvqfZKoTE6ab2toLuwGxJbRFiSDhFAyGA/cLwo3w26/rNxoRbmI0maer5ioNTfDVzYUgiYyrK/pypTPbWfJEJMJxH33Kg5vksBmzzEW6HXX0H33MzZRPAAfTmxNhUpl21yrgVy5v6WMximXqyA3NVDnri+YmQEwABBRwQp1zpCx9qaBH5wk4OlURfNqNx6GA0BH7+L4BJjNgcUCiAoGLQkVsLBYqsE38Az0WgiS0zMVKLRcITo6UulXXOuTFpjcQKeUn+u6M+2ionljGSWvzL1VZMlyFUr3HkErrcLdTDh5nD1llEsCliy1QudjVFxfzR29djVnQc/d2wpemZsBoVLwvTbM4s6LhaJ5eEpO8QXTZ2NzZeq2a3GlA1KwtBsk46I1Y0eMVLYY+fgtYDoDTs9Uaqqie6zlrgwkKCt3V6+mad+qFqk6CxMJleFGb1DN7yr7vVXt+H1WlllZSZ2wTZtgwYr2aTi03FKuuTkoU85dutpauSs5H6tVJluClb0SxT3IXTMo2lisFUqy9AoSBF6uQFcOlHEmSZTFMdap35JE0R0KcgPnrmGUR01HdDPTWNkqWCtNVTpznBiP1FfGOOUEa7NkQKTFvABkn3lNOXXXqgwn1/tdloMNqDXVWNkNhcQY2SrGneXVu4YfDTlUgfzk0IX8vmaCbxvAWub1JiBnIKvYuARkUYeD/Hoi+j4A14no7wH4XwC8st9u9QjHXVPE7eMkUUEMZiebqAhgJAmSm49nd4I+15alLVMtJhN13HBoKwO5lmClIA5AR1eBk5OU6zxLuc25tGr6GgCyPGqoHSGZYCXNk4JW1EutRGsWRzcwUFngFmpSNQEVrhvUPadksbQC77jV5NkZeLFAMp+rKkoFlnT7e4tca+7k6yrt5p6tUUhYcppxhETxZORbo80GJkkAJ1WZsfhxcPc2glHqLIfXZIOZjCGgaAz82E272Oeg6UcAICqsMdZ6OhyA7joCzs6UnBKl+V8bUAzg9nc8UnInZTO5KxgnVu4cb9DaseS6scs8QZRmbpGL5frIedvXNcqnL3fr4MiQsSLm5M6bl9NzKMhdEzj3kedz/ZEeB8xpnI2mA8rpDCJWsTTwYkvUnJe/hJrzVQEfcXgFq0fn6Tqn1wh/DFsrtU6NahRld/0wY1YpejEgJcRobL0/rCv9yfmsvpJXRXHyaCPy5BR86xai69fV13rdEoM4FzeUvSHpWDVZWNysSbxaIjqdI/mYZ4De/AelXVX3Yn1sgX/tokB68/ss1bLIuBfkJoe1o4qZvxXAGwD8Fyge8tcz87/ru2N9okyJMpZck3KMkwQUK4oF3bhLH64HecECaCYBoRVqns0z1AFzbYoHyko9HAKnmrt4ZWJdX0YxthOHqyg7MG4mq6yulsoas1goxd5zVze4QRnF03CZxMGBCj7076NnIci42QratRYn3V8AiD7sKeq+VwXc+J+7Qu4s0jkrR9F5novN9tm3nnuWdPPa35y4LqtCJS6gElYZNM8/isDTGcQT7kF844ZVAAvTqelxZXh+ZZszGsSgyVhxK43cjUYgoRa9jRcIluVy17AddTO0p8axAtVRAIzlrUp+7FjVcQlr261acHWbOblb02bmOMpS3azMBbnrDBmrvOs1BSAfe1x9p/MbUxSB7pwUzuGl1lIz3qZTyDsnymLtHWtpSM455npm/TKy7dYTsGsLCeUhHaSZJMx6W9t7UCGPufSBUQRxeAXRUz9Ulbt3xnhm7V8j4ya+IUMrjCLQzVt49GMPUpktkRlLjamzQS5Y6zM6hHt9YyxoM+9dAlTOKEQUAfhZZv7rAH5+O13aEsqsTMMBaDDA/8/em8bKkmTnYV9E5FJ73brb2/v162WG3TNNzWjGMyOIAmXYpkQaBmUDNgwBNkUv+kPAMLwAhmxAhqUf+iEIEAHBEGERoCAbskALlgzJEAhStE1zhkNyOORopmfp/e13qX3NzIjwjxMRGZmVVbfu6xnD7nsP0Oj7qiozIzPjRJzlO9+RoxF5qzb9C0C8/grhGCdTqNG4Mp3J4xpYvUZKZRSLFKCY4rBsF1pKiIMe1HiSQxdkHiGmn3uVu6Vot79h5PeVN0Mpp5V2FT+V5M7PGTU98gsGSoqtszTf8DYZpt7CZyNA+vSc8IjztPJYGxlbi1q7Bd9/Lt53ZfHHzDgYLz7TQqW0/b1/rdL9kPOSY8x2ispdS0EsvRcAyCltztoYPhyAeukGxLwHzBZQ5/1KxhOrd3yx3MxJbAwBvVhSFOdgH2o0ydvwvkgUxZsnhfVgV72riB6X9Y4FIZClldE7/zx5Me72LIjTIcYBvX2+5gEB7zzeuNf0bpd79qJuPj6zbEAVf188/lrvdhTrbDkYjPedUuCdFmR/4CKyKknAGbGyaNMMyxZeboS9SAmmNPR8QYXX9brJNHp7hU31e+fSSUJRZJfVzXJcsr2enx1crVwGUyVJofDtIuakix9TkQeZmYwusmytKYj/u8pn4s1dwl5E6AAAIABJREFUy7ji6hIC43Aqhfq5cvdf0Fl7/1JSBHkDK8/aNVmIQjS7lFktOM+lffBaqmWrgay1loyxOWOsq7Ue/b81qB+5+Iamv3GEAVgY5uB5QYUgYBx6OIY+6ACNCBwAS1LCInviqlttAZDZyF1FqlECvzjBeurKVsH7vdIrDNB8YypFrz2qpLXq+RdQABfJM1EbHgZQ4ynUalmEO5TGBWBzOqh0X8w51QrgHGo6y6v3qxY7awhXXHPtXW6CZFgpR8Es1m0T3qt8HmuYS7j0Lm0Aaf59lZF9LevCOGA2ZbZYEP+xgb2osz54GCI77kBwDp6m1ZSAWgFak4O7wZj0N18eBoAQOePDx9gkbCq0kP34IegdWN4idpdiOvrNZty8H611bAC7jKfiPGv/3uAMVw+VUUFLybHd8ONrvfs4olXevEmtBxjcGslYzkUPUE2GMUILM6DivboosA5cpFfN5i6iT/tSCeNrHS8LsVAlJiRvTbZ/2zOo1ZKCVyYY80LwnvJjKheZMkYMU0lKOGx/3/XmPLHLVM8ze19ufvrZ3puH6Hx3SIGycr2LCXL52eoLHc/y3lUOBAnvc3sfMAb4ZZ/hFZJdclJLAN9ijP0aDJMFAGit/5Mf2ah+1LJp42LUsECNTTvNLHNwCL1YAG+/B95uURFeVTGMMU61obpx0dESHCMH7VPkTA3H4HENvNumTmKMbzVA88t5CgTAKZXlF66oCN5ZbAosCE1BIi2gotYlOrbymMxYq+hy1k9NylkowliuELz6MrJ33qtOmb3IPbi0E9u8eJTGX7khb7oPL6rt49IuouS6FiN288sID8u1iQYaGi/e7UFPZ1APHyOYL4j1hfNCJMplFaSEnk7p+E2LPctZVFgUQfWH1O61XiNaQmA3mjJfNGENKWWJIkzkY+odCwNHfXfR5ujgVtvmnXMwd8A0e8ds/axKb5jFT1efY61gaJOBjerI4LXeXUIKEJZSwV0tJtpDzqjI1eKCVysK8lSk/je9DxZ4RneSuAI89x6FgNa5Y+velfe9c4xRih6b+4AQYCD8eY5RXqeQu+hZVAZf7Bw081GOxgheugPUYujHz4rBF8uhvqsD7GdupCRHJZVIjluIbh5DPnmOSsfW6DPLsgsj5AUn0b+uuWdLjQhgbey038qis/oi2bRPoOxiIP8T898nU/xFvRZTgY3BH2vGIbodsP09sGUD8uQMmeFoXBO7OZU2Cpp4ntcJ5EV0WjsPUty8AQTrnMPla/hjLp/X94IrJ/2GcW/anGCi6JAK2hgvjFXjod2hVVHsspSgEHbhWL68j+DdD7YaOOVzVJ3X31xpcagglzdeuls0VeYcGj9NvdW7ts/dOEuFY+z314vMZvHel85SyNncfCYh2m2iVYxjZM9OoE9OCxuiFf+duahThThcsB8hSzMEt28CYQjGDG3YCxhYBaiTjc5epHf5wNbmrdW7rYV+VacylGlbr1u+lv/ZZaU8di8rt9UQ8f5egzStDXcDow2u9W4nseuc+btQoNVsQt2/BfaddykYZJgudJrlxeUiLJ1ufS11jBPKGJgWThDHgNYmArvOeEQ6YwI9WuX0c/a81qCzumSZNkrZQQdJfJGMiHctdx2tINptIJPAZGbaTReDKm4NusQ8K+CWJzOEUYDVqzcQPjvB2qhsgItxd8+bjGholc/96ptz17dYcMcaY6LcxItcLMi8li0GMmPsJa31R1rrX3mREzPG7gH4uwBuAlAAfklr/TcZY/sA/mcALwP4AMC/o7UeMALa/E0APwNgDuAvaK2/Yc71cwD+G3Pqv/qiY7pwzJ0O9GBIf9sobxgAkynSH7uHkDHoGUWH9XxexBya6AwPGVirAyhNmClr7HqeMi0EOq+KrdeBNIX2e9z7UIENxXCFfzujUwIg434n2WRoekaultLBR6TFpZXGZI1cZSqLdzI0XISXFDwaLKG2paYvYXDYzbkqcr/2PN2iLQrHut9ueUaFS5vnsnPF8bXQ/G82ig0+GCeKxMkU6afvItjvAE9PAQB6tnBzHMjfD+MBWKNNm6jBGJfFpmlt9Em0WqR3s7lplrCFIu0iMansnaNKG87hNq8ELppMUhEh8q8tASbzTpcbxXMeAexkVGwdb/lvo0vl5kFrUWP3p17XpYsM/Gu9210K6xuK7z8QUDWBIIoclalaLBG0msR/7AIt5lBRMrTt5xYWKC3W1eiaCQCxIFyDRbEwMFConCdYG/ieNVKt4WvF/davgfG++zhSVXAvHz+hDFMQuGdGa4dvvG9xYP1AUMkx1LM5WJoiqN+qrGW6LOShynFxl4vCHA6qCffMa7GDdV7LZtn2dP5X+wdj7H95gXNnAP5zrfUbAL4C4BcYY28C+K8A/LrW+nUAv27+DQA/DeB1899fBPDfm2vvA/jLAL4M4EsA/jJjrPcC4ylK1SIcBmANomez0RudZsjO+ggGc0y+dA/LL7+O9HOvgN+7s75QW3xfELjoV2XES8q8RSrdJLLTc8jpdG0T3IoB9IxjJgQVKnmLmPvvsuLdlx0PM3zQhWpkzzi2x7lq5G2K5zkMNuqnkgT86fna87rwHOU0XMXfrlrX/N5nBbHvwv69dn6ttrNy2J8HIVH32Ur66yjWbqIVWKMO3mrmKV2toJcrqNEYwXCB1e0OFl96Dcsvvgr91uuuiUFBGCf88f6eayjgfwfAOXDO4WMM8rwPORxSqnnXanj/1D9svbPGgZmTtvHJLjqhVstLbawf16goSIW+O73Dhoib/5wqntsL6921rEnZQdFKA2mK8HQKFkfkkAYBRRINTSFvNorc4lXZB/9zeHugEM44LuDDzf8dX7+/N9rsY1VGwTPWd9ofKmTbcWu6LxVEq0WsTR4DRTkCfqGel/Y65wBICXneh/jg2cZ5bvcpt19tmdtbddlbm5TpFmwx4X7GaVe2nKsk256GP5teueyJtdZPbQRYaz0B8DaAOwB+FoCNAP8KgD9n/v5ZAH9Xk3wNxLt8C8CfAfBrWuu+1noAYtP4s5cdT3FwGyb1dAY9X+RNLGwVKwD93kOEU5PKkxqq21g7j1YUFVaTKfR4TFWwQNHgVFRIZAvfeC2mQkDAdOAL14y/rQuCPwbTxY/Htd0m+pbf2JQ0jyIyODQ5C2vjMYutXSxsN7QLo0AuSkCpMh5FUH7rzYoFsvC3v7GWnpVPqcNNlzaXJkN1tGDtWlqtnWvTvTiHx6Z6X8DQupJiDdeVoUPkzC3SarGkiOAHj1F79wxMAzzVyNo544UvOkuhRhNgvlj7zl3ObESWNcPpnWlI8sKFKp7e/TDevdU7m6LWWbo9Osr4xRRvVny923Cuyw3WMwC8/zuqr+ACFF+Vk+tHLl9E764d06LonCqQcZZHfJcrwM4rS2MWx45GDYwRxM6eZgvlKIC8uZbIU/pArndr+1h5jzPrrt8Axqcoq6rnuZRs2+/KTrcwdK+mmQcTwjUyEa3WbsYxDbrg+Fnjn0UROQ82sl4xtsLz2zD2guO5aTz2GZrnraUkOJnHkmX/u967irJt9dIb/r60MMZeBvB5AL8D4IbW+ilARjRj7Nj87A6Ah95hj8xnmz4vX+MvgiLPqKFxwYCKWDmAJok67zsF5PUaoDTUcoX0X/vj4FIj/voPoCwNVVW608IshID2e9brnDTdNzwplZqARRF4QA0+ZJIWJ/omw9Ccz1Yka2lahfqbk4MMXD5SZO9RpRlgYBOi1wWCAPL0HJaZI7/13Ovn7TbkaLxZYcuLIlBs+cs41vBW5ciTvykXUm0ovF87fve+q7r/lqEX5rz5InjB8zOLDo9EXgxhx3gFNutL6Z5/nIEDyMFo7TnxKEL2Jz4LxYDoWx8i/udP8gXd38y8jYdxBjkYrc93rcAEtdllkrCKajan5h5Gz4NOi8ZxSSnrHRmr/IX1rqAPxnhx+MAt84nXYiAIoBfLnJljw/l9Q+VjR5Gr5jmz+OkSM0FVQwX/HPZvGD3+OHrnneuTKrvonc+VD9B7cDje2RxYJcQ3ftCDfPNlBKcTYDSmyGkQwGGHjag0W3/njFMwyLJZSJGvtQZu42B35pjs/DzfLzxInsPze7UfDqts6wx2NU4rnsWmIlwWRWBJ4u0fGvzuLaS39xB+eGr2N0NV5zurF63x5e/tvmTbpM/mbh3cdLyjiOMMYOHmGqWKY6l4r8gNb9lMYLKjxSzqxae9SrLNQP5jjLExKJJcN3/D/FtrrTu7XIAx1gI1GflPtdbjLZx+VV/oLZ8XP9D6lwD8EgB02P5Wg95NSO3RhukcFA+dAlLRBrq/h/q/eIzn/8YDtKNPgSmg9nQK9t5DSFM1Xz43GKMiB6VyDx3GAzeGscUdOSaL2RxstSpWmGq/SYAsLP5uAbFpGxY6XNG6sYlLGWtMCMJkGqUS7TZYLUZ21gev1zxlXY/kytEIwkSRNyqbLpLEu+O3DoqvL8yl76twlWRcaDiavTXnwyw+XrrPxyhbR+ZCQ8Jb7FkYeAVnn3y5jO45sQ4I7MZXrETXUiJ6/wTP/+xL4K98Cs2nGYKFRPhH7zvGieLpDJNEEBCWsozrM5/712RRBDWeuszHpQv0zAbEazHkbF6tdxeeItcTqw/2OfBGA7xeJ/rDLcWijDPCEwJUz1DBguf/1urQD4XaiVVwk5t7sdzvlRkaeHpfYWDvxMrhznWtd5v0TksJXo/yoiy/OCvNwOMYGoCeTMGX+9DnfbB2C7pRB56eFCLI5sD1i5hCbkiZN56wxleW5kwj3nvnjQYZ34wYNNw8Agpz3RW+hkFe/OczpFzmeW2Z76yU6WBCQJ8PEAyGQGgi6twEoyy93C5j8ANa/n5nouEuULbleFvb4KK7gVeMy8Ii33TpWCbyLonFG+Tgcehag1sH85rurSgbV3GttdBad7TWba11YP62/97VOA5BxvH/qLX+h+bj5wY6AfP/E/P5IwD3vMPvAniy5fMXE29jBlBITbhN1m5USQLLNrH/7TmefSXEw381wNkX98BuHq9vgtbbyzKqBA5D7ysvXQ+K+HDT1UuZwj+Ya/uYXgD54mI3koroN6/XwI4PIe7dLfR/L0RUvHO67yofUd7rnsc1assbEs5Pr1ZOkSrp6xiHnM0vVDRrCBTurYTxqj6whFn0x1xKzzIT1SBjKCxErKuOs+Oy74BH0cUpYm8sGxtUXMu6+O8uDByWlD7gpkjmKY5+b4SszvDwpwI8/lM1ZG/eJ+hB+XRSmm526RqxP/1Ak8Fp9I7Xa4XCQDmeEDTpksLrNbAbRwheurO73m0QX+95XAPv7UFrlcMINswtrUyrZZPx2iYFvXXO9eWd6MI9sbw7lztnEDi98y5eHoyDhjhDSIjCuS64mWq9uyxM5JMsjOcpdt8ZMRkONZ0ZmsUM/Fkf7PgQ6UuHYIsVGbClrFrlJYRwVKD2d4W1HesGHAtD8N4eXcPbG23Bpd0v7Xwtf/8i73hXKjgA0MrMY6mgJhQIU7N5gc/Y/HC3i9vAlmmR7jIltsanvGaVIRPGobWGbBUFX9U1KZi17uS48a8x8LDC8VddfmRPwLBS/B0Ab2ut/4b31T8G8HPm758D8I+8z/99RvIVACMDxfhnAH6KMdYzxXk/ZT57sXGVMVTeJPAjQFpKIAigTs+hJ1ME3/kQd39jiaNvaHTfXRF+qyz22CShlJNShfNppcHiGPzogFre2pbUUkL0uuAH+yhzOrrFwqZENlQVg3NguYLab4Hfuw1xsE+Y5l0xRaXn4DaqMKAOZoOhMzbdNe1Cq/JIkSuW2WHhsIrJvPNuHG8ZVuHDNMy5qsYDG603WPK1cbEi3tFv1KKVBrLq1sXlc9j/W8eq7BBdS4WY56yWq0L6tRCFffs93Prfn+D46xo3vpEhGG82AHWWUqFaRVU4CwKw40OndzbtGOz3IO7cguh2Lg838PXuoEN6d3jwsfQOWpkmJua84+nFUR2tXCTowoirDQaUCm43FsRdJGaz9Q14naVAljm924hbLUEsfDylNYy2yga9cwW51wIAxfbrZcfN4oWThGpAAISnU2AyBWvU13WpAr6iFktie6jF+XWscWZhF2X8sVKmz0Dg9hkfB6u9CCtgAhfGMb4Qn75BttbymLoge2+828lriGTJXngRZ8wapX6mGqh+Nva8JQcUKEahGWeunqlyHFY3VfV4tZSFYMIavvs62LMTD/KLyp8E8O+Bmox803z2lwD8NQD/gDH2HwL4CMC/bb77pyCKt3dANG8/DwBa6z5j7K8A+F3zu/9Oa91/0UFtpEMxk9B5aJxBJynEjSM6bjRG+PvfR+e3iBpFlj087zwAXArFfWZbTUsJTOfU7tYYoqLVBDpt6FoInJ5TwVq5IM7DNq5di3Fa4KZTiCwDWk3ido0iot65JH2V5YulSueMuJo93NeaQpbTozYFtuX5+FFqIF8omBBQSUW0rLwAlBZ6Z8wrnbflZXmRh0ozD26xznHsw0byhTKlpiu7RNZY3oQCjIPFFG2/dFTuikpVGl4cHVBr6UdP0PnoMS34QlRHiP2Ff5NBOZ0RPMOwWYhWE+i2oWOCOXEpISeXg1noJIF6PodI0x+O3mkzVwGoyWR3vCG86Nqm+eZBF3JHN83Xu034TD817EvpOn5avEDJ5dYpS8lnUunChz0VoWU8ErsVvlTonTXKd+ai/iSLzrvo+cEDuy4xzt1zZrUYmC+gDrvgcQQ9meaBBXOuTdcAZ0AUwRafM2sMZqnrKstDRvSjWgFaUzG7YTyy1GNyNncFc249t2Lnld8V7iLoXWGYW2ZUvebtRQAYg+yTw+CCJnrdkCWM7w5zzO2LxugXRa5wOs/mtYeeK11fpRq8HubtsBfLynvPddyzeQpBCEM5W4KBrHUFvcLyIzOQtda/BVTihwHgX6n4vQbwCxvO9csAfvmHM7CSB+1NmNyo8xRRa6DTAnpt4MMnG1NGVmyVMKvFjubGKoI1utUib9fMwoAwX4NhPlktHksazkWjPK6Djx23CPNN0YwpOzkFH46cQtgINH2PglKuPRf7Z5a6RgV2PLxeg7KK6Ef4SkqkTOvXjQuHOV8hxQuvZ71PCVSCUBT4i+07UzmsggUB5HTmcF2MM4d102lFJFgIwBQSuTbh1oC3HrvtZrYtmOUcB1OYwk0TGN84uJZ1KS/aha8YEMfg9+8B/SHUZALAOLAVuuenZJ0ue0LdL2luqSShiFe7BT0cUYSot0cGwnS2+8bAuHOEs5NTsP4wx0raQiPnI28w2Ep65xeM2s1UpdsL9Oj+yBjnYVDJq5pfToPaTCNfH0xgYNsxG+8fKMDC7Hl8vSsYZt5x1lhmIipcn0cR+F4X2hRNbxmY+V9R7wqFZFddKiK++d+iAMnRyxVYt42sFSGcLxzLS+Fcm4IejGpvRLNBf5fgO7xGtG62JkdLWWBF0mkGB9FwgSUGtTKsNEpT9meSw+cKQZiPa8xxD/cuJeTJGXi9Dq0UdJLm+7WBBPlFj5epXXDZFM0gDvaRnZ6TQ1ymprT35GeYksTBwBjn1AF0Ols/zh1uHNb1QeTjECGYiJ1NQsEkj5v8ihvJP8oI8v93pSo66Yw1UdiY5MkZ+HIJ9cpd4NMvg69SsNkS+vQccjJZO49W1DmISUkFQ0mSb4yMDFxxdADVHyI4OiCvezIlDKRnJDo6GGsYsvWCFSaEaQgiwTttsDiGms7WNkjfsN4FhM+CEFCaugh229D9IaWSNy2OpUVKZ6a47aLnb54XCxlYQOk5vbrAqPSv50WjiREEOcQDyOnAggBIM0pHWQy1iRK4iFoYQCsFFoa0oFQVFl20WGjlDLhCpuJ6odkqBViLcSq00tDnfeD+beiXb4Glx4CUCE4H1I69xHDgMgNb5g5r1qGnMwTHRwW9A4AgCqHKzCs7vDfebYMlqYv2+jpKm+lmZ7ryOQAQvRZYqwk9GOU8tBdFx3a5hmdQ2qJf0WqR87hD58vKMRvdY2HsHHwWEZe81TsIAcgk1zub1pfSGdJciDxaKDjK7AkX3Zevd2vG0xWXQtS49Lllh7CBjezhE0RxDDmZgDcalXtcpZOnNbVlTrOcMs2wYDjWB69YzLaTV2me0VOLJe27BiqjFssiY1QYEMwiy4od9XZ/EJu/M501eb1GgZVWk6LnpvmOSvUafvjS4gdgggCoxTmDR1bhoJb2N/ssmBBQiwU4Y5SltL8tjYtHUc5os2XMvNWkTIJ5Bu7Y68Y7PzoM8v9vpGJD9XG0vNWEHIzA33sEHXBk3RpUu0H0UGXRefGDlhKs0y5GJLUCi0Ko24fIvvwG0O0ASQK9WCB46Q7Yp19xx695/L5RaA2ILHNRGHAO1qgTlrlep+I6Dx6wFX+19kioqxir11w6W5nCuzJGqVD45uGmLlIuG2XmzQYtloZrudLAKcAeVJ4irnhGBVgLADmd5YUoCaX7/IIgmAITbfCSOkmg05QWi+XKFRzu9Py8qL1/j9eyo5QyO3IyAR4+A58ukXViyHYdaLeqG4VYvfMb8JTlxhHkl94EOm1gsXR6Jz77qc3FfReJEKR3e3ukd4bftLxh7eSY2o0wjgEuYDmQd9qQL8hslYWHAbHNxPGLZTq8+2PCi0RW6l2yrncwWRupyIDyawiSFGo03t34Kemdyyhd697aGllex/x3oaWE6LQNzVvL/GDHecE5kttdWkuVDQoQSwVvNUlnrRFog0AerM5CM3xHuTBWrQhKIPOshwtC+HjdF5XZguaj7XuQJMRMY5vvaGsoZ4UA1E44eQsDiiKiYzTPRo+nYLWYmGcqD/Xqa0xkG4waIvFGgzK63u8Kz4DxHENdFrtWKur2q6Yz1yDNnc/rG3CV5WpGkH3xNzFrmAYe16A2KcjRGOLtD8BiKvDZVi1uqd7QqFPU0nQmAuNgAPhwBrV/AH16TtQ4vT3MfvwWWKZR+x7Wlb3sHRojUS0WztPTkyktKrb4T3AwY6TKyeRSm4UrbusPAUMhVTjeS9uVsUpb8cfesY48vlEHt9XUJoqxFs0qpZr8qDp9bUnuCbOmVktaUJIE3EY1bBTdX9CEoHR4kjcbgMHEOS7py0aAPQPALfLXUeRq8aPGWsHh9H3DazoF3p0j7HfzIpJtKf8NkA0tJfh8AXW7DX3Wh57PwQ/2MXvrFlTA0J4toR+VyHF2yBjo+QI6TcFqsWvswQBAGQN/E1bffZTfiy1qUsMRQTe8JhgXyYXYQR+ra+BIAEjvtjBkVF+suD5Zh6Wgd/Wac0h1mjm9s8wyAKgI2mzyPnTshaJXVXpnsmtXXjY4aowzj25UUIQ0CgFjKKrpNI/GXyRBgNV+hKjdgp7NobVyxrGaTGk+e3PTLwq1AQgbFS587m072ekZRLcLPZ267OBlMPrbRBsmFEd3lli4Ux6IKURXzXPbBV7hoBspFSVafVOzuWOy0sv1epUypt+eSycpYJKjPpyoDONyNRBV66Uf1JK0jsFAYHi9XuR6vsJybSBXiB9RUbO5abmZuHQs/WiLAcg4RSMDAcZ5zv6gFX3+/BQ1qSCnM4huB6s376F2soQ4HUO501g2C5FP/PKlTKSKG/5PF/m1kVHGiE7H33B22Ai10nl6xi/oqbrXkvHqinN2KZDhzBUr2lQQE3k0Y804KOGX7XWp6l+QkWK6HanR2HSFikzXooAwdYZ301FQSQlWF4BJMWkDxeD1OlFsjXfgQPbHBxQMFbe5XBvHm6UKR8g4eL1ueG1TyP5g7b0XxOLqsLmgTD5+hlgqqPkcvNvB6s07qJ0swGcrV7hXKVU4TiOW+omtVjnmUvAX1jsmkDvf/r3uYKzTUDdjnR1WF3BO4S4GxqZUtmOgMU2OWBRC9ge5zoVUi6GG45wrl+mc+i3LCLMKOKwyhKD09ni6O23iJr1jl4BpXBUpOeuucFkrsFqDcMiMEbbVzYv83W80mLMMMmbEGRyFYElCEeQoAm+3oKYzwJtrdj/0ITFujzRwR1uDY9d80WoBgkPs7UGOxgVGJRaE2xvkXPRYPCYWrTgViRZaZNt9TdO8tJnZTU3DCo+ccP+83SZ9MXzsTIitECpXtF5uTGK5pJsN6MVinX3Cc4Y3Zq7sXmr12gT1bEDp0pzwn1C5NpA3iDVQeb0JKIJaWKHFnG3ciAETpckkNGN5VW4cA4JT1ObJU4hX72P+Sg+153PoP/wuMs8wX5vYJdyt/UxnimilCrRI0nmPL5JqdHAQW2xXRf9S3lS9hZc24guK9KQEE6Fr+sDr9UKRot+Fyx5nKX/KhoxWGgzSdMzT1BRCmUieTZkpRVEzIVzjBYQhmMU6Wm/dUO9RdXAF9dgOUoB5XBvGLyR2zopO2xS9KTCpNkdV7byzkcOqDUcIqPM++P17mH/qALWnM+g//C6kwcLuHC3zL+vxovrj2lnv1rIv0jvO6xx20Wm8ObdN91xnzDAgbnCDP73UXLW6bp1Vmzq3TSUYo0CAUsZZoFbvBb2zGaR2C3oyJYhVljmmgheRMrzqWveMbHi3foRWK+1gdXqxdFjfciSxai4yIQClECzM+67VaC0OA6j+APzebTBXJGuyFYJDr9LCfscE8swg48WMkmYuE8HaLYj9PWSn584pfdE5s/48DMWcB9ViXOXf87yD7K5rhXMk4wg6TQs0quCkK/SOcoPcrmMqzchotTrKGXRiuhXWDNTSOhl+kb/PaFOVwfSDSwDtf5zGKpfzHLZxxeXaQPbEwQPcBxzgnKLIYQB+sE/YnPkcer6o7KQHgCailMBsTgtOkkLP52DtFmyhAn/pLhYv98AzDXz3fViy/8KG6BvL5fSxF53UqxVEtwM1nxexgD4m9xLiItdx7KI+F7Z+Lv1/0+Lhe/283YI+6oGlEvrZqWvcsFE5C0UL9JGNgFhqLDAOvVjAFnn44mPLVarp92FI0ePRGGo+z7mpFUUa17DOF8kPId135aQKhqAVQYhaLbD+9a4GAAAgAElEQVRmA6xepw3bw7auyZZ5B0ZV3+xwH4tX9sFXqqB3axX7pfNuEh7XnM76MIEX1zsUmDAui8N1Dnr5a4v/DQNiiDjoAlIDT56D7QLl8LNF5jq2w5ejUlwsjP7lescSopGDS2GT3mkpIQ4OAUZZL9cOHnAGyqXkWu92F28+F2hN0wxMpGDNBvQqAVabuf4Lwjj0coXayQpqvw0+XRGPcqcD3IqB0wF1sfTnmFdvUoCiwXMUPfYlALnRqjT4QQ/B4T5lIKW8sEHOhSLzuWd1yO4tVRSUruh9m964PZgaCmnTEMz1NAhjsEYdajQh5yDzosksdEEhC1NinAFSQpiMti08ZxnLM7cyv7aWW2gm/UCVhbuUoujXAZ5rA7kgPhbP0astSbHVaAyMxvlvt+EgGcEq9HxBWMfjI/IepzNXjCY/eIjo/Q8pFfnafYhMgZ0PIM/79gLmhKL47/JGZT5T87kjyicPEmA8yO/rss/Cr8gvGKYV5yopUoFPsnxe4+2Kg31grwN20nd8mM5DN+MvRMEYJ5qbGsEmtOcI8FpABZHNBjCeGOdllp/LGBxuDD7emHOgFgN3b4FzgGWKvOnVCji9uDNZxQ0Wn8u1XCwbMMNMCII1jScuQrLNeVprGuN9B60gh0Ow6Qzhux9Qav/VlxCkkgr2+kPIMsXbDhuE3bT9xjAFvbtog6m4hm0b7b6nm7rgNH5ka13xiJnHYI/DAOx0ADWekN5dsD7Yd1GuLRDdLlirCbQawHAMPZtDTqcOz1oed0HvtIJeJWA3j4AbPTKquGk7PBhBTSbF1t0XyRXfyHcWb74VYA4moqmWK3DD9gMhoNPVxuOdaAVwjuB8Cn1yhuSPvYIIwPzVfTTeOSdMM2OF+hJn8JlrFvct4uS28Io10Qp6uaTi+XoNvNU08/jFH0u5GJYis1lhvcmjtOl6MG2D2GY8+rV74CdD6NE4N5yThLKdUoI3G4CFiJjveaMBdnxIkMDlyu1/arki1iUDz7BRZFc3U3pmlXUJfvDNc+zBeA4bsbZMfqIdn+YnR64NZKBaCU36kAEIjg6gV9SIY2vFt4/FTbOcZixNoQZDsEaDmCck8R/z3h7UzX0gU8Cjp5DGG/bPQ6mSCmykZxzrLCW8rcNtWe8Wecr5ksUqa4q2AeJRJb6hW/4NN+TmajoDmy8oDWvTysy0FeXVyiyajXwxNfgvS8+GyRT67NxRC7nF3xY+lXFcWrm0EhZLgqg0Y+goAEslsEpci1bfK9+6SFRgsq9li2x5njyKyPhKUuq050dsLtS/6rlOBP0C4vgQ8vYheJJBP35GG02V4b2DsVzEmpsxeilS2xxjo1RBQUpd7XZxcAvp1QqoiFsbFkvCS5tMiV/YduH5PUfZrm3y+SlYPzB4yiTfeF2R83pzCgtn0qsVFS2P5tAtqqJn43lutO+6IW/Suyu4oVdKVbbPN5Bs1kErKhprNamobrGsnEtrwrjpGqsJajFNoE/PUevUkR22Id4+rxyHlgBjOSORNaCdYexnTN2lqJhPKE378mJJe8nHgObkz6MIkcq/orE6R9FGV7ftqfa+ggB8vwf9g4+gLduLlylxUXpWXH9YFFGhYBgAw76hPlTkaIQBZcMaDajzPhjyJlm0/ycFutNK8fRFS+qAm/dJ8AoCHczk8vCzT4JcG8hWStgdNzlMVIPtdSAOeuRtLZZQw1F1hMPipRQtFjDV4vz4iNpWS0m0N80GdK9Nac73HrrIy9piX5HadJ/7l12tyGAMuKvIBWwkfMM9b8JqOm8+jzCs0az5ClNhSFg8aBmywrttiqC/chv84SnQbYNNZsTCYVNQFhdZGpOcThEcHEBNZ66drzVuWKsJ1m5BDYZ5wQ/j1L2phA21i7PWCgyCjLDhiAyGOIYGcXJWFgluE//Z7IAbvRaStWISrUwTFw22vwfBDVYvSaGHo2LjFi/CalP+1RfhNEfqdehem5qNvPfQFAH6qd3iMe6db3j3lewRdvPfpncbzuki0T5sYxdDrzDO0oUZpxb3x0fQ9ZjwoFEIPplBT2em2cAFu59J97qMjIFGiOND6OUSajz11hzjxPiYypLeASCox7NT0ud6jTCrs8Wl2DvcPft6d20Yb5bSnC4wMkgJrFZUO5MkXgGnZzBtwv9LCZYRPlgzRrRhqxTB+QQqTYvtms21WBDS2q1pn8gLtUuF6b5+Kk0FdIslGeRhAKb11uY4L/Rs7POAzc6U1qkLnGdrsIu9QySv3UD0rAEMRmCGPtRROkYhzX2/2x1A+9CD28DpyATV8rVNLRZgSQLRbhErhgm60fmiHLPsbqQaFmPH6TsoFBgkTPQL0T9+wuTaQPbEVwT6m5p9yOEQIo6gDrtQkYAYLsCyDDCtKJ34MAO7mGhN/y2W4HsdqMGQQPlpCvb8nNKSiyWCG8cAgOzkzClKgWYMnoKWIwIszFNBBk8G+F3Fqif6NraJShYJOsgZwO7f3r37JP0F5g1GbBuQCmg1kOzFiNN9qDhAMJkRZML3rCuiQsHBgTP+ebMFNJv0HoIAiKm5CQZDV4kLTQ4Kk97G7d+rMu8mENSwAKDFRinDz5wa7Nz6Y9go/n1fb9S7idmEc8OQOx7qIAyAvS6ygxZYpiC0BvNhAVUOaoW46GkQgD0/BxZLyNmcmvWY4r2Nm+yWSLelgmI2Uur//0WgTUpTq/TLGnreGAtUXs7h50AtQnrUBE8UwEB6V8aGXjxAgjPVa2BZBt1ugC1q4IZTVS9XeXGvR9+1pnde1FHcPKa2xpYPPeHkDF0milxeb66lWiocKYdBliAHcjwBC0MUmnygOK8qZbUCkpQyooGADgUwHFE0tITxtwXXNupJqf084+BYGLzCS+swWp5ebaFI7OMX6ZWPLxTLVkSxfUOZIAnrBrNoNoA0RfRsQvN5ucrhUywEtOHm78Suw6A9P2s1Mb/bQnMwIyMY+f4oWi0gCilw1+2AaU3wTbNn63K2tCrarXMMsrsHKXOIi/IalUl5ZXXr2kD2xHmMAvmECAMi5R4MwdOUvL1VslYAtiaMg0UR4R5NS0jmMWGo0cS1jw4evATVa4EPZ+DDcZGIvOCxVhSMWYiFbZUMkU92Tv/etLBt2oSrvORit7PCjyvvvfCdTTmbNKx+OkFdKjJEswxqklM65TjOYvRZ7PeoiG9FfJGU/iOst+o1CRahTTtSIaAWA9cWFGEIPZuXHA7v5HEE9OrQgkEHAViSgc3mwGhCEeqL0uRlY97+vQOG9VqQZ0Y0c/+2aVbZH4DN5ggWPUAZ3uEt+P+NUS4Y+jQbaTF6J/cpmsxWK7BRySnc4d35USbrcBb0ruocF5y3MIZLYJCrHDP7rHSaAY+eIjqNHZxETWd5ynfHuarSDGy5BKvXoPbadO0wyBsNGAMZQoAxysDZoryC3mkFNZmCPbgLJBL6oAumFNgiARuNoeT0coWD9r593OQl7usTLeUspCcOE2yKQllvDwgEMBq7+pv8NNUBFa00NcCIY2TPThAc7SP76BGC8AFw0IN6+hy824H0A0rOqC06ujmMwTBslIJBroDPZEVs9PRjS+mebFdbu6f6z2Ejw5Qvdnw3D8HGM2C+AJSC6HbX6GKtU+kODULIOwfQDJCPntCzNedElkEDYAC0pEYj2rQFF/s9MqbnC3fOSkYlH8LJ8zUXgLNJtOU0v+KZ0GsD2YqFV3gLBhMCerYA77SgBktkZ/21qGb5HO5PQ6HE63UwxqEZJyM5jsF6XbDlCqjXoFt1qCAAH0yhzweFYgHLn1gZWfWMSa24q0Z2+L4SrGAzJd2WR+IWqiJ5e+U9F8Zsi6VMJNyPzN84AhuMKII3GtPmGgQQnQiqALHIx8trMbFNmOvxeo0KqmZz+m44Ams2AM6RDUYIjg7A221HP1Vgxyjhu8EY4Y0BsOWKmEakotSz4ZjcSbwof4GeawfM9lUXvWHOsigiA261gnz6zP2uslDvAtwvEwK806LIWC2GbjeghIDoT4DlykWnNgxwo6Hlqr7NGMrXdIVtOxpqfrFdAT6yjVfcj6B5MDG7TvC4lnc4W63o/wDpXSuohhN55/Z1m9dr5LSMp+DNBjVCSjPHJgAgb/vsR+HKemf+z4ZTIEnAZYsKZifTnKVkF32p0Ds7VvvsrrxsggOYtdSx9TANpKlpEjJby6hsDLTY9xwGCPZ70AFxFWM6ow6vlinIP97SlXnUhgWKN53mDrO5BxekMQwPtpAQPjTxRaUCXqFVlu+zvrHo2wBlW8CsQ4wz4LCHxZ02omaMYDgHOx8QA4dhx/DrfGxjEp0pQHDIWIAnGuLGEfRoTIarg2WY6LvBLbObxxBKQddCcjCzzO15fqbAf5ZuvbT3IARRpbJ8n11zPq+gXBvIVmzUCiZa6lGeIAwhXr0PnA2oecRiWV016xZnTpytUgKM0TG2kK4WA1EEebMHAODLDPzRc2TGu6aFXnoK6yl/hefuT3ZS4KrU85ZGH2u/zQ0Qu2jmaZYi/Zz7fQm76Yjng9BFAlkUQisFddAC6zYoerw8oPRQFICdDcFMxGLNUAoCigDXTKeyWgzBueNdlYMRLfIBNWfQ8wVYHNMCn2W542OgKO4+BKfocSah+0NopaDP+7Rx1OLc6QDW33XxReTPxaau/OjhdRRru1RkRcTeHhCF4FFILBMGh2edKDfPPd1wzSEqnjULA7DeHuQBtdD19c6+Yx+PeeEY7bW3/kasZUK2SUHv7Ck3QZ02ic0i2c2WcfDDfajjPahaiGAwBwKzKQsBftIHS9KLjXAzPt4mJ0MnCb2LGQUDIPLovWMcMdXwa3zQgowgdnQA+eFD8HodajAq3Ya+WG8u0rtr2SzWkfIMLhYwosis18HiGMJk/NRFeFaAIpYGrsYyBZUkYHvUeprVa4AtpLNQBN9Y9t+b5+yt0Z16TheLQjLkfUiPrUHY4khujPb6Y7MfCwHGA8/QNLaBZYvJKPizBn1kHHyvC7nXQOP7pwZSmUGZ1tIIAoInWd52i8+2BmmWgWca0Sih4n5D9aaWK4psKw0NSTSpqxXYdAZ0WmAJ1UfJwShfdzbYDv49+gEKC3PZGgi8QnL1DOQqQL2XOrLYKGb6wvN6HersHKvP3kHy1iEAoPP9Efjzc2TPTzZfRytK/UgFFoYQhweQ5wOgxaBPzyGSxEUq1WJBnreUUKYttE9aXmlo+R6sVmBBDUwrQ81jGplYLKTfLWsHYy339HM2jPXnVYR++BRbhciZSZ0zzgkrvMywvNUEBIOYS0Tnc7BVSkV6ZjP1Iw28XjOUeXNaWOo1YgipxUCzAd2qIzg+hBYMTGrCck2mZCRHEUWlgoA4j22E3RYPCQE06pi93kMWc4RTiXiwAlsSDjk4G7oW3j5GuvD8y06LTRteLy47CwvIcXGcrEIQhnG+QPbaLWSNAKueQO0sQ+2dU6inz6t5crfNbaWB8QRiRR2+9GwONZ8jONwHlIYcjTdGyLaJS396BXWVelc1VqAYtSoZd5cx9vy1wlK6aRijWykyWmKBxf09aA7E50uI8dLp3Ubx1xvGyUFtt8AEJ+hSHOSwpLO+4UIOIZr0XHTqGfuZp3cAEIVY/vQXICOG+skKYpEBmQIfjKFHE+jForoQuurZ+XpXXievssHsP6vy3sEZ4cZNVJN3O0AYYvqFu2h95wz6rL+Gja1yoqjhBadAQ5pC10Pw/R6wWEAf7gEfPjFzZj1Dm5/Xy1QyDkezKvNr5HSDplGGEOBCbO+CedGz0Z5xWvHc8qh2rlt+BstCQXgYFIsdwxDidAxdj8CWlKXkh/uUlZyZaLCBRjLTCdfeJ795jKQRIByvwI+PXFQfWhGeWym3t7E4pkjydA406kCjDt5pQc8W3n2JtfvKs20cLOK0P8cUgCr8/irrDq6igVwlFhtnvFcW02JBkcgICALUnkyQdHqQMSNjLAiKx5cWH1Y3mDzOgFYTmM4g7t+FPutDzeZgC8JSiv09zH7y01gcCBx8cwT+zkPCN2sb8dwc2ckhA6bKH8K1VdZZBmY2zI18opu8xJIn7yAaflpmbXMyEaYoogjRSrkokm0tyxp1sOEEjckcCANgsUT28Aml+RbLfDwGlqElKPUTR64zl+U/VtMZ+CohLFazBjZf0ULBqFc9a9Tpb1coqcjeDwLoRLu0kmzVwDIN3QBmtwLMbwSIRwr1Z0sEAwGbjq6eNt6GwWxLbs9ZKEdCrqUgxQ1XFKIxajCESjOET4bArS7mNwKogNE858XUqzlZNaOE9zs5GLnPxX4Ps5/+PBb7HM1nGRrf+JAYUDYPtvKcYNb5Y2Caok0FvdskWzaeAm6Q7cbO4FLk5v79a6vzPthkiuhJDHTb1Pzo8VNoIajZka/X24QzyPM+Vco3GsD+HtgyBWpwUem8QE/Rc7H3WtI7aAWMp1jtUdBh+Kk6giXQeJ4gni5Id6v0ppAtwxa9s/Cza92rDgjRc+HdDhWi94fAAWU1mQbBjrY1zykJQdxoX5zfaSGOQwSDGVh/DKUUscb4e0aWuiY7YCHgBUcczKg8bhu8Moa0ix7vMnerpOyM+pCmDZA8a8i7qLrnENu5yaIISBLIu4fQjCFYpjlEMEldi2jn1JrOlirNKDC3WELWOWo/GNLelSRUlAea27zRIJz4cgW0KSOm23Vozsm5nC3WnaHyrZtosc5SIAMZx1LltKnXAuAqGsgXbDK0yWqDb+JAvQYslsCHT9DtU6MQNRhClWmpYDcpi4UkqhsWR5C9Fvj5ADjep17yN44w+/xdTO8EmN4FVjcy9L7JwCdLaM43R8fWboUgFcxEjbWUYElSwDblqbSKe98SXaFnEa39lvgZk/XP/TSq5SE2Y+PtFtBqQtcjiia0msAoBaIQwasvE8PHIYd6fuaMJWckSGkiE7R4KLOwsIiqrDGaAMMR1GJpCONTKlxYJdScRUqicUsSMt6lNb4lEIVQNYH4dInGN0+Beg2q3QBfpcD5wBUxcZNNKD386miKqbCGVCgTzV9LSQzWUCvT9ck4qlpKwBRYZu++D/GkjoN3u9CrVXXjFjPHbUt3VMGfhIA46mHx2TsYvxxiegdY3TR6l2qC2gQBbUZVsglikWVQNhrm4/acwV7q7rctomn0yPEgW4MvzbY6yvmpjWHBinhq1miYyBBoU5US/PZNYL5AsL8HdXpuOvddYNAzRjCxkOi59LMT0vU4NpjSnJ5NJzlVpmOvsRKF9Bwadex9e0Q8yM0adMDBn5yZxkFp9Tq4g94BMje0rngErCBm7jmnwWQ4NTKiMF0m0J0G6o9nBIHrdoi+z5dNgZosQ3L3JoJJA6MHAW59MEJ61EL6Sg/13/4+7akldhVniAoaW85SEaxBHog2NXPXY/U6RETF6PmafsH9X6A7vhPKTWSXDlPQC+n2tPIzpf3eGPkmQLX83MvgiULw9beBO7eAZh3oD8EOegS3MBFj3mpSXwD7nBkDogirrkDtaA/i/SeUlZEGspgkUPZ3IBp/1GKwhYDaawJRRPtfkhC3v+9s23fFOO3t1k4xvQmgNNRk4hid3HFXOBtz9QzkKrEGrulEI6dTsDSD2N9D/yfuYv83TRQyy6DnC9cG1omXjmHctFNdLME6LUoTtyOIN+5DfOtdsG4Hyas3cPZWgPnrCZBwHH1N4OjXH0I+epKfz+IqPe+08B3gDD2HNfTIwS0rhDMevAWn0IhAF6Od+S0RITlBNtKceqocFfMMApi0spYSvF4HN1F0NZ6Ad4j/OP3C65jejVE7y7A8CKACIJpq1E9WCNMM8uTUS7dJKu6QErzTojT5YkGpQM4pMq812GgCvHwPshlDnI2hnp+A9/bgujdpDV6vQ6cZeKsGzI2SRyH4UkJ8+JS6PY0mYP0hRbeRRypy2IiHDa9YLHSWUpMIr0DqKpKr7yxVTodbzxn4S3eB2Zwo2M77FHn0i1Toh/m5tmB1eaMBdXMfJ58PMf90Aqw4jr4qcPQbD6k4llG6+bLjt5v6Gk6YecVypc/87phrjBUGrw/OaZ3ZodOdWwe8tLWLSMUx2I1DqFYNk/tNrLocPAO0AKKJRu10hSjNIE/PL7xdxjlFCuOIaN7GU6ib+9AA+DOTjjf3yBsx6S3n5GS2auA2qh5RrYDqNoB/8Q5wuA+cnlM2yBRnVj4f77kX/lnSO2ekX+tedZZQ54VnbK9TgLycfqkH+bN9xH//Zez/1iNwxqBOluawDUXHjOA2KhLg0xUWN4D0sInlQYTGE2JvWP34fQT/xx+5Qy0+vVA3Y8/tMzp40W4XudXUupyc4hAQ9p1fkvVkm9ggitKeoUz372Oy3XOs18BFkwJqtRjQQPiNH4Ddv4vlvS5mN0Psfa9OsKbRqcuesSgkx87yiBscNwAwpahPQJZBIyUqSUlrGYSBLHIOeXMfEAxa5DAXFhsjWRQj8dZGoaYg1FRLJ4kLLvF22znpOeTx6hnGVq4NZMAZoXy/ByxXCOo1qNEY+qCH3j/6FlZf/jT++F//A/z53lfxuaiGvz/t4a/9rX8XN37xa84Qys9FBV78xjH6P3EbzccJZMyhogh461WoWICvJF76229DjaeEYbx/G2d/+i6iyW20f/P7hEu2G6NvAHhGGXW+oQWB1+tFTzDNCJvlbd6uAMhgn7YuEnYRMAuBi2pZKIUxsMvpS7/aVy1XYDZlxBj0yRlYu4WgFqF2JlB7PkPj90+Agx70s1PI0RiZuzzz8IocerYAC1sUPf7cG8BwBv38lCilDnrIPn0PKuIQiwzzz9yA+vEbaH1/gGyvgeA0BpvOPEwyRR+wXCE9bCIYr6Du3UDWjsnj5gxZQyAa0L0H7z+llrxpBqCYJrTPgTB4BjsbhcRakmXGscjyAscrushcJKLbAQAyBpPUkOfXMX3zEMP/YIr/6FNv4+c730fIBD731Z/HK//ZAJh6kS0TVXQRewuZ8kTN58B33sW9tynS6esdcBcHXz8H+/DR9rRy2SlinJgxbMYgSQyPtmc0+9kli0veIlpKyIlHA7Ujlp3FMRUGGwfVGYmrFeQ77wOMo/1+C50wJAN3uYJOUsjRGHILNZ5/33I2B1uuqNvabAF9i+ARUED28g3wRIJ9821ikAEciwzvtMAYYRy5EEgPmxDvKfBnfSRfeRN8JZG1b0MFDDzTCCYpgo9OoM7O1/XGRez4Rr0DzFwyWbWrrHeVDEY2mtisU8TdBD10q47GqcTyV3sQiYa82YN4eOod5gVTfOhBs47FZ25D/ZdnePdrt5G2FdJ2gEd/RoGpGPHzt9B9V6MXhW7+UwZQuaIwlWaEm5cej68Ht+PNBhl85n3zRoN+a2p5dnnHPk7YSSHAk+umpSoEI0gXWzDnEFs2DTe3NKPCfQCYzsCPDlB7OET21qt49uUGsgaw/12F/mdbUEEbR3/vsbuePO9TcXkthpyZrq+n54gmtzH4TAdZrYtoehN73+xDff9diAf3oWshIDVktw4dMGSNAGk7gOYAP76JuL+P6L0TolA1DD2F+4IJBhrMMYsjikLXYqheB/rtd2gPtu/aexdXTa6WgVyxwflesJ7NKcVQrxP2NUlx/m++BQD41W98Af/bw69g/yvPscoC1AYVxXMmisuiCHo8xvTWHaw6McKZRr0vEXx0Cr3XwtmXD9CpvQKeSix7EU4+H2B5P0Xz+yE63z6AGo3zYoRS0w+7MNGCQp2tHAzARqeEMDyJdHyhfaRdMH1PuipdCS/VKwjE7y8ItFF5EW4bFRPcQSB0krpoO6/XsXzjFvo/FiGYA0AT6t4rqD9ZQAiB4LUHhIu0aVr7TNMMfH8P6LahH9yC+OAZYAwqS9Em/ugdCEbk6o1+E+gPgXoNQSaB+cJVAltoCItj8piXklKJz0cIvjsEQCmvYDQBP+hRodhsTo5BVbTTr5pmFPGDUlS8lCTuetfGcbW46unFMi+gBIAsQ9YfoPkb30Ew/zH88pv/On7xT/zLuHM4RPK4CWCwdq58/oMM1JIhyuIYw595A43nCcRCYn6Q6x2bCUSTHlrvfbR5sJuwfMsVYXABKpoJgjW9yyOacutGY41oFpgT+s8E2MiwQThMbvhRCb7giqEMRy0/2AeUgjo7p3Wq1QQLA9K7R0/Wi1ALN5kb+bZoVi0W0N99z30ujL7bQmO/aQrjLF9T6zXwpXUYNaLvPoKaTBFHEa1N5h7lYrkZYuGzlVToHbxnfq13WI+cWsx/EABxRMGGKAR7eor5v9TDX/lLfwcTWcd/+yt/Hvf/Vq4ThYCI/1zTDOE0w1997Vfxj48+j6/37+P82y/h5X+YYvJSiKPfH2PyoOUcJgA0h1LfocXGrBvjDGo2pywiADBG7aVtxpSzakegJH6tzPq9iEKWUCtFASKT0bBZUcsv7GhIbd1SJBzUCKsVdK+N9/6tOm6+9QwnwzYevRyBLwSYBG60mpDn/fzdCJ+mkUG/9RqyGsPJn5R446+fITvuEMafcWA2B8tiIMsgQgHZiFD/zlOIV46RtUMqfP/2R0CrQe/U1B+tNQ9KEoKDtFsUjU5S1/wHcWz4/ysKPK+YXC0DuUqsNy0E9GoF3mhATiZUQLBYojaQGLwW4M4/4eh8/UPoX5yDNRrQ0+eQHhTCRTYAqhqPI4gE6DzMwFKNxrceA60Gsl4Di0OG2e0Y9eeU6qydAb3vCbQ/mAJng+pUUOnfPkaKRSHRnFl6NV/RpaTfBsWiO3+8VUV8DucLmKIaioqJVtPxZqo0vx4NUZOCaeUwhCyKyPu/fYToZI5ujWN+KFB/PEFyTA0+0jfuIdmL0EwSw1Dg3asQxBf97BQCR9A3DqDqIUR6AHncAfvWOxQZfukWkGQAY8hev4vg4SkgONJXb0KMxtRxKElI+aczaK0ghjNKSVnYhhBAsw790k3oVQr9vfeoPW9/sJ6+9zBdjq9aRGCc53zOQejap15LSby57OBARjTMs1ssEFd0wfEAACAASURBVP7mH+Lmb4fA/0DOy4+FH8Hi79bO5c35tct1Whi+zjB6EKN+kuvd/tsC4UQiPltSRO0y70srIMsg+3OnU1ZPrd4V2vT6eEVzv4Wx2nXEZF0A0EZV2uDWhiFpDhfWDa82gNVrSF69gawhUHvWA1tm0AFH1q0h7UZorFZQD59sjxIZ6Ac72IfuNMDnK2AwcsVDMIWx+iwFPzqE7rTAMmO4LpbkbA5GAGMQwxkyKQnz//AxrafGGKHK/Aii1YSezojvvBzUwAV6Z+BZl6LHuypinZ0gpCzXXhN8OqNsl9LofrDC56I+vra8geWxKhTEukBLKbDCajGCJwP87uIB/t7vfgV8LtA2Rc/HX+1j8qk9NJ8s14tWbWDF7KHKQnQ8RiSbHQr2O2TAGYMSjJngxe6GW94tTlDNg/+dLRj2Mk+s1aSshIUqII+iFzJDPKCot4V/NUOcfbGH2gkD/vYR9toc7UcJkjZH8/0xwTR920F6UCIhoEKOpz8BNI5nOPnJm4hmCp0fZJT1qteAKITsdqE5w/IoxvLTL2HvBwvwlULaCaC+8ADx+RI8k5R9tQW8gFtbeL0N1mpCHe9hdVhH1qR1MPznf0AOgeVdvuJFrlfLQC570b5hqxUB5rsd8BVFU7Knz9H8VgAZ30Hj2YoW7NEYfLHMO1ABbrLbYiMeBGCdNqKJRvOPnhJWqNWADjh0wHH8BwSgDwdLKsw7OaPuOpxBm9QRnZYZQzQrjl8rals9nkAlCUSrieDuHaiTUyCIiRvRi0DrLKUIzsqehqhp1oj8S1glmM1ZpRlEs0GtM2GOs9FlA6ngIXOGgSseDELyUltNqFCAT5Zo/N9Pwb78GiavdymdOg0QDBcIxisgq8BxHh1A7jchpKRe9mEIDpPCZQx8rwuEAbJmDM45+DKBqgmgFiPrNZE1AogfewDJOZjW4M/6FH0wFdc6y8AO9oHpDLrbhGrVAKnJCL91A/JoD0IpyJMz+Fg5R0fGOJigroms04JuNyAWCTUfSVNgtG4AXguJ3ZQscb7NULAgpPbDvTbYk1OiokoSU7yVQNy5tXYu5YpT16PHAIDFEvd+bQ5ZF+t6B9o4tGdYVkr5c8bBGg1wA0miDnpwaeHCOISgSv7yecp6Z9PG8A2ECzapcs2CDwUyWZjwZArRqQEKAAdYKknvhgtKsZcM66p7Z0JQO2Fdh27EYKJHOisVUS6GAfTJGfReC+lhC0xpsFSBr+rgpyPXfVREROuH+QL81g16jso8mzCEbsRQjQji0RnYfJ5HFHfVOwB6PKEGKBdAWj7xYuFG5RoWwakoKw7AUnpGajJB9Dvfw5/7r/8LyIjhxkyB1WobTusVxSmN2Vs38Ovnb+DV/0lBNhigJGY3A/Q/10Ow1OQsecdYo7PQ4KYcTXbjB9T9m+CPTqAmE6J32+uC7e+BmQY1jtZsBynwK9vrCAGdug0SvNkgY5QLYpyaznIoip8JsqwVBuLIhAB6XaRthptfW+DkC3XU+hqLI9ovh5/tYu8Hhi3CfwZGf1m9hqQXAZ0U85Mm9kYK0ThDsl9DHAREaddoQoUcsh6AKSCcaSTdENBAOM4Qnc3AxtToyha2u3tPEsIwa03OK2Oovz/A4pV98FRB3LsL+fBR/oyu+L51tQxkK/5LN16sVhrY6wIA+IOXgMEIfH8PZ185hObA8y82EP3km7j120tkIYeKOaJ/+nsA8sWCcQYWN8B7e0ju7qHzIXGuAiAQ/nyB6HQA1GLIJ8+hspT2qyiC6HXBGIeaz113IwuXgI/Jsv+PI+BTDxAsE+jTc/R/8iWkrfuo9RXCuULUX4HPU/DJHPrkzEV6WKMBDIcuSmu7BZXFRqXBOEVzErOIGjaIcuSL6GdisAcPwIYTitIuqWsXA7A6aiBohBCdOmpPZoBggNTgpwMyPn3nxVskdSDAp0vo/hC4ewtsNAEbz6CenULM5xTZnkzBn50Q9jEKES1X0MMxAq0hvn0OdvsG9PMz4NYxLRqGc5drTSmzxZK68O03wVcZ2LffAb9/F0hSiMkCejbPN1rPGaKNR8PFWDIJKEDHERVWzNLC/LgWT/zo0RuvUaZxvADGEyCOMX/rNqa3Q8SjPUTjDME8gwoFVMTBMwXx0SMAeVSLNxqGe3UJrVWxrS0ICsF+51sIACgpnd4F+z3auJcrsKMD6A8fFgyybRsE4wzDn3kDyx5D/VyhdpYhmKUFvdNJAld0GsdGrzeLaDaIeg15pofXDeY/SdeaGVjhn/kU2GwJDMfEvmIi4VpKqMUS7L2PiCc9CKBNNihnDfCaHWy7byGQPTsBP++T0x+GtMlqbVLRZPiykz6i4ZSMsDSjgsM0j4TrhIqz1GhMfOZKk6HBOMCXYNMZRLtFa0gpFb6L3mF1cWHjlRD/PZbfp1TArWO8+wsMr//HK2r+IiWWP/EGan2JwesBBp8Fav27CJ88zU9ZLjwFoBYLjO8F+Ojde3gFAJRG45sPUT/qUVS1P4a8c1Q4zs4BXq8X6NosJMeP5jIhkHZrGH3+ddQGEvEoQ/xoBP34GWVaBHXJVGcbGGjKz6T8bMyYfaNcJynh9Fcr8N4eRLcDPZ/DtXO352C0dtimVYhCJMctTB5opA2iLqQbBpgEwqXprWBoXgmD7fH/12tofu09tD79KQQLoPt7jyFvdKFCDr1aYfHG64iGCYLBHJo3wVOF5tsDGmuvDZZKsjUadbD9HmWznz532TVWr4F120geHOHsszWEM432wxrqPziFjqOcxceLkF9lXbp6BnJFFMh52WkGtd+CbITEqNCqofEsg4oYZrcDzB5kWLwTYbnHsTwE7v4zYYpiaLPlB/vQRz2cfnEPk/sMD/7Gt6miVSqo4Yg8zUYDuh5D3L5Bi1QcQTdrUPUQTGqwZQJ89NRFY9mG6JEeT5G9fAR5swl+u4twpjB4Q2D4BgApEE6bCCdA/ayLzns9RB+eAYMR9GJJBm4BF+sxNBjhx0dghuxfNWPweQIdCgQfPQfqNchnJ2tePqvFePKne6id76Hz3hzB6YQ2rzRFNFyBz1bAkxPaNMMAajQG9vYodRQEhEUtYdBYkgKMQS6W4I+eEv544aXBD3pgWoMxRh35kgxYLAkeMpqA1WuUPpYK7OmJK5qz1HgspE5taLcQnM0o0nF8CIynFLl838OKWS/fsIKoNAMPKVKoJyl1ixoMwYIAarXazD99LQXJejWogCMMBXVIlBLx+RLBQmK1FyJtCaQtgazBsdxnaD1WaPi4/0YM9tp9nHypBxkBx1+fACUDGS/dgpjMc4PN6J1sRNCMQUyXwHBaPcBNmyqA+RHD+I0MAw6IWYhgGiEaeXr3dAwYdhqdpHm7XCNlfDq7cQRx/zbAGFQzRtqJwBOFcLAAe/8R5KQ6Ijp6s4u0sYfm8yPUHk0h3ntImaQooor2LMsLmgBqnmMKkRx93kVzlTOITtvUFSio6TQvzF2ugCm9D9kfuHS2e0e2oYpWebEv53nXLx8jyRlwTh0O/Y5gLqOWJFTQtU3v7LWuuFRlHyzWffJGD3/hrf8TX23dBSQZbjpgGL8UwHofk3sh9r1z2XdSMJykQuuphPi/YoTDIXgzgj7ogq1Sgg8c9SAGU6goco4bCwMwzqjYzmuwsdYcy+wH8cMBZn/qJgaf4YCOUDs9RvPZETofrBD2F5Df/r5bmzcFI5wz6NiePKq5KCR4ldF1+cbLmN+pI2kxBEuNvd99Bmlqg+wz1FLm0DxbRyElxDLD3tsM+28vEPzBD8COD2m/e/gE/OiAglUGOlRgwNEKulnD6tVDtB8pNB8tsXr1EGIhwZeSMOMMmN+pA6hDMyBYKeiX9xEOlmCZIio802UQBvZReAaLJVizAbHIUBtohHMFninIow5EfwY9NvUD5jlcQyyuBYBZNNIULMkQPutDjyfgwxHq303B6jW0vreH1e0u4vefo9OMkR40zYE8xwPHMRmRS8I3sptH0I+fUVFYuwWdZUjv9qBigWASk7enACYl+GQFtjBNMLI85amztACtyBcQjegJtWeVe01Ev/s9tN++idXdLpb7oYtcB0uFrBEgslAKzsCCmFo82+gPo8KCPDqqobpNLO61oAWDDBmicQyxUoiadehmA/9Pe+caI1l6FubnPafufZ2eu2dm1/ZizG4gGNkyRpYCGCItAZE/SA4CJCSQFSkGIwVFQcmP5B8/oiSOFCSMQRBBghH4B4qEsLkkThQLFsPu2qyxvezFO7Ozc+nLdFfX9Zzz5sf7nVOnqqtnenp6trqr30dqdVd11anvq6r3+97vvXJzQjkOC0bzTkaUQDRIGVxZJd4dIi9+DdncIvuObyF75kkqmx3kzqaFfaytWmywROP1IMsW5XvblhxUraBb95CVZaKVJVheQq/ftCTF5UW4fB463aKtZ3TxXNHJUBaqphCvrhAvtKwUTrOJLtscZauNvnLLEhsadVhaRETMxShClGXoTtssZaGLX9Qf2Hs3GKD9QZHskGfSR6EepSfp3Z/qRhe5tW7egCSxRfz6m8RpyuLKsiW/hHJI2UqLdKFGkUgaKl5k1Zh4oPTOCOli1drklt734flFopUWUW9YyIYkGdF2z8opZUo2qVTnTOYDlLj0xR3OfaVGb63KsAVRosR9LeROLi5RecvKKeW1motC/KpIpiNrb6Zos0bnnStoLCRNIakLrbsp1U3Gyl+NDS9NWbjRZ7BaJRpkZAs1KivL6MYmsrSInlu1Tnflg6WM3Nmy055eX3qSYYKsLJtVME2h2SziQXMrcra+QXTmbJG3gAgMhxajKSOrIIC0mlTqdUtSSpJgQZbCKkgUQWbdRvPYZBYXHix3zUaI3X5AdY5TSBErX6nQPR/z2V/9fi5sPGeKY6vFwvM3WHi5ZesocPcj10bPzetaN+pFMwwA4oilF29Tv3aG6PYWcnYF6fTRVh2qsX2GC43xBj+hiZOW953JHILyfpdlXPibBI2E/kpE+ypsv1NIaw2a6zWW+FbSL3/tvgpdEbqYhxaGJNg9lRokYveaKcdpXeidEVbTtKgcVRwK05Ts8lnzhPYtbKF/dYXdSzXOf2nb8mve/63EvQQZpqTvfy/ZMCP+u9fH51iKjUaV+q1dor4ls1a+8hqytmqKbrNB6+UN+7s/IDu3StTpk924ad6zWtW6yPb6JqeqsLhgoShJijaqpIt1+ktVGm/usPZ/Nor8HjmzCru7lrQXDr6nXTkGV5ABE5yoUUfPrqDfeK0QVAFkbRVt7yLtDvVX+kWt4ihTtKS4Zr0+0d11ZH2D1VcrnFleRretsYhqht4zt2e8e5nqrb4tQFlmTSy6XUv2CRZHmdwIJy1XmtmptNOF4ZBoY9P63W9tU7uzTj2OzYoTLETR8hLp3fXCerMnvig/Lebl39TavS50zHWUtWpE9zowHJLeuEl87WppaLZoaqbQ63PmC9+0uaxvUrv6Duh0yCpW2SPa6hBnalm++SbX7ZlbPMRe7ilBt71jSrOGzlz5xhsONFm3S3z5kin4/QTdbsPlC7B1z7oDDZMi1kqqoRFEs2HvzdIC2rBakrLYCuXgrMtf3tGIagWiuIgPIwuvXa3YT2ZNJqRh1hIaDWQYKnEMreQXwcvgjFN8D1+9TrKzs1cJ1czKLWajphMSCdW1M5bkJRGSZhZT/vXXOftajbMrFp+elMMFgOqdNtLuBnd8kLtOJ7RlNzmOV5ZJykrk5KFm4rZmSvTCN6ikKQuJWYeLuqNB7qjXyIIScJCavrKxzUI/Gbls0yzIwM5YRYvJa1Sef5k4SUwJr9eDPA2tvOFGZDIz+fpZsGAdRDnO6fZsbKoj5TjvmBdFhfJVKM1g3qF72+Slo4p5p9ko9GusM2lQkmtVq0MbSudZWMcB5C6vjjIY8sDauPPMlINdntgYLS5Q6SqrL7VtrcvUSpU9+Q7rPlGv0r/YovVWMvbcwvVe+ry030cXGsTt0BI5y9CNLaRvHePIFDm3Np6kFxrMlFssS2x7UOF9KNH+jos07vSJdgcsJAln/2gD1lZJV1vmNcxG3r0HrbV5nL4OTOk1Q9R4AuHKczehEpOuLVj4ztb26LkyatAVdQYWwli3yhK1ehVJlLRVpbI5pHZjy8YWRUS3Nk0hDSFOiLWKzkMZAWR7F4DqMLUKFOfWbM/qWwlJGQzMK12rEu10bJ154orpAklihp2lRZP1eg1t1Unztu/ViN7ZGhpBvNYibtSIegO4dgnaPWg10Xs75HlFxXfoFOMKcv4FSFM0JH3pTrsotE1mgqzLi1CNkdshIJ+wMKRpUX4pbYeY00qVKFPL6s7d+AtQWV2G9W0YJiTlEIXwHGCPcjx5iituDwbo2rJZhvLNSATpdCEkLOSJS+nddaKV5SIus6isIHnb1iQkreX1HSF5483i/ak8cdWEp1Ylfs+7od0Zla7KE4mSkNgwGFhJnoWWWXurFevs096FW3cp6i6KmMLZ7ZFsbI4r62UXdHD9ZsOEqDJEoii4gUbZ2Nn6hll5sRbU8vp1s1CsbxRxjJHqKFlBIqvlmiRIf2DJeuGzBMjubRPnh4xyU4p8g9gBtu6NPqtcaQ8LIVlmC25wn/lJ/P5YdZTQMnVoymG0aB4a7faKzUvKlR0gfO+CUhTco1GpxNjYa7x6nXQy/recMZ8MLQHoIcgT8aRWK2KhNQ2u3DS1Q2keKhU8LA9KGktu3hof+z6W68l55LHNWZrCbqe4Rrq9Y3Hd+zFxSL4fmqYmE7klcKLigERia+HdjdG1c3muVMbLfElE1t4df4GiCpCObouM6tweVO6yfZq3nDbKVU1ywvqugyG17Yytpxc585IAauFojQrdS00at3poJDTfuLenWlPW65tXp3z9NEVrdWjU0XoVnnyHVaPRFbJGhXizw/h+VxlrzGMHy1GFiDy0Jl87K7spW+9pUt21pMH0u85S6WQ01odUhql5oMqK3ZRwqKJ+dui6GEX1Uc3lPKE9tZKR/afO0VurWm3hBBZf7JbKrpYMQ5XIFFIww0t3QK07QG/eQi6et32oXguHjkW0UYM33xrJUDjU2j5hiZPa3kXPLCPDBL27gSwv2nc81KzWEDpIswH3tq1rbMvKKOpWCKNcXSG7eYvo0gUq6/fQ3Q5y6TzxX91AnnoC3njLmsQMEwv/PLOKbu+MNekpwk/32ZtPA64gg33wcUzWrJI+dckC4IPSablE9rcMEuTqO8wlGAu8eh0JMX1WJ7Fh7vdqlWx90zpY3b5L3Kib+zBJgQEkaRHLB5hbP44tqS1YfsbqfJbJF6m37iDB5U+txvDdF9FIqLTrRElKfHbNNpcktc0zXwji2ErYlTejsMmTC6noqK5svkHt7JJdPku8sWPWoNBppyw8stCyk3Ke/FOrQrVqFqBWy2436tbgY6FVWJCjasU2UCgy3Yu5hjqUkqbWsjpJoRKTrW9aXGNep1Iz65S30Bq9rwMLo5BgKYuW7D0vEoPyjbYSI3GzSPqxeE2r/DEZIlF0dcoU1Yki7OV2pQdRbBz73jx51ep8ZhlRP0GrFbKmFcOPdkMIBFiITRQh222i0AhCwudvLVtNxjRJyNrtMQUp/zzz8mkSRaPmEmoW5cLqP419Nob42tWRNbQcsjQcmgKYWqdL61oljLVvJ4RVlJTmIlZXxMZYqRQJbFm3OzXJTyIhvnhh1JZ9MLADX/5dLZfNKj3H1r3wPU2Sfessj54TjR/g83yB3ANVOgiMlONRB86iHGSuaMTRmIs9vMjISlmKcy1aRz+s3J3CTb2gfECB0XsTLK3NWz0WXg0JYmmGdjrEL99g8e4y2c1btM6sWim1yc8mD4UJSLWC9IYklyvEG1vI8gIySNBqDKkS94ejx+fhFElCkbxaisWdrGyRj7Xxwms03lhF61W0GtO70CStRyTNGKRObW0V7m6MLMjTPvPCIBQSPEWCNyQLVSxClYpMSWsR8UDRsbOFjsmSpinSDRZdEbJm1TpBpinyrqtkUYTWY1uz1JpQAcTVarHPjTU3Uls/JI7N07LThisXUBEzst2+a0p4M1QWqVjFDElSO3xKhKyumMIukXUiBWjF1kcgAp55ysqhPnEZhim6FCFnlqA7sGpOUORvTK8XfbpwBTkg9Tpxu0fWqCGbO9Bqki00kNffRFaW0KUWev1NC23IMkRjy+KOgxKXW0ZDp6roiSvQ7ljoRpqSbbfJe8iTpvYlzi0qlUoodF8ZFbmfCKkYQ63Mm+52yLI+tHepxpGdKLPgSs3dnGFumiuemQbFtWLKQZoiNIoNtYjTarWKOC1t70IcEW+2LfGtVoNp2fghwcoUzsjCKEKyQNreJV5cQDArb658Zp0O0eKijSm0hi46icmoBqXU62Q77dDrPq+7nKH9PvHSoi1AnS7a61soy+KiKcBBOSZJ7LOBooGJUHIVVquFG7rookQVyeMZg/IzikEbuZCLmFJAtLSglB8zTLzk1CRhs5Usg0FWWA4lSZGNvn1m+fsZFDmJzK1flFbKlchabdSitdM1b0gppj7v1jfaqGUkH5mgcWaxew9RcUQznbCKhnADVTsY1uuFlSwvjShhMy2ekqak7ZG8S17rNZ9z/tg4tioUU+ROM7W5h9e3spVhHQgyhZaUAiiamuTvq3Z7o5jS/RCx9Sz33kTR2PXsOt3isynGF+SvnNSFhIZCwXNASYaKkA0wT91waOtrLqsHkbv8cZl6mcWcsqK7ukzlm3cszOyJy8iN21blpxKZIeipJ8wCLAL3tscNIZGMHyQzZXh5hcbrm5bg3BuaBbVet8NnHJPcuRs8lKGBzWBg3r/QHW+0No7qDReNhDIlu3bR4pt3dpEkoXWrZo1v1jeJzq1ZKAd2wMx6/X2rvRQNP4YJ2aC0Hk94nVpffhPtdMybeO4s+X/yEqmFwWRzy2oNN+pE9Zol4q4smXEm3zM6XQvV3G6bLlEaz54qEcMhLDStCs7aKtIPa2CozCJBESaSUYnFnCQpmpuQZfb/es1yq8pd8zK116lWLWSjajkS9Pqj9Ta3xp9yuTkxCrKIPAt8EpOgT6vqLx/pC0SCbO9aLU2AXp8IYGUJkhTZ6cCKnaw1dAAqsnrzLPFev6iLKCtL1sEtKGVm4bIktKjZMOHOXYyleqd7lOP7vSetkdWT3RBaEYkpYx2LT8qtqUX4wGBg80oSO5nmyqAIRde+ZGgKM9j9YQ50upYZf/aMLZoT8X3a6dhBoGb1j9PtnaJEXLy8ZItYHFvCYogXjFaCm2e3YxvuJElisVfhYEGakty+a4k4obFLtr6JLDTJ2m2iVos4JEIVbrxKhWhpaU9SSBba5mp7SLS8aIvmzg5Rq4XUahau0WyMd+bKFCXPtp5mpSjFXpY3bWc6mpG9+s3R7fyzKcUG73Hph++1hvJgDJPwuY4Uo1yOik02D6GZUJ7GHnMIl3z61u3S0EtWsjC30TTNU0OPUegAjG9wmo1a1k7jPqE62a2743foqIudTmumEIk1h8AU3YPMPev2RtYuQIvNVMbim8feZ7AqPiWFqujylyRjFmnNQp5B+Vq5VT7T4vEudw/B5F6SfzejCF1dpHdlGa1G1Jab9M/WEYVKXiklEmo73dGhsbDs10bW3qCIRkMryUkcElKvXLJ9UxWt16israJv3SG9dy8MS5EilGKiWY65bUdjD7+z8yuW1B68uaiax7BfKhM32L/EX9FYq9U0BRYgHFDLVusoNONg5TzRlYtklciU3xs3izAqex9iRCLbD4fDkBAecldULS459EQgy5CL59BKZCXYgmW+6FVQJO2p5bz0+mSvv0F84bwZeXp9C1W8t2O1jENPgmy3gzTqJke5VbsavFiVeHQw7VhTFQk6CvnhPj9Iq5VflIUW8fKSeeAm15tT6I0RPQGLiYjEwNeBfwxcB54DflxVX5r2+GVZ0++WHzjEC5VcSI8SdzMR83Xga5RdQGX3xsO8/uRrHwWT45+iAEx93LQxTaPkGrVFt3Syn3ALjp6y18U69b3bM5Tx9zXP1i0/N7/+oT+DE8if6O9/SVU/8KjXObTsOYfnFG5c88LM5C5Y8POk6HL4y/jD9qkEMhEKM3bfZELqlDjoaQ2q9rVY5vvi5NhKa/e0sd9v7mNj0nJ1qNJeNGVPmBzfZLWHPYfkMiWdIh9rbvEeCyvKdBR2WArh3O99K9/eM949Ux/taUVC8eRnQOm9nNP444PK3UmxIH8QeFlVXwEQkd8F/ikwVUHew34K3SRTvnAPpeBOu85BXnfsobkQxuNCPMl+YzrKL3H5PTjIazzs/ZOvky+E0567XxUAKE70Y7/3eX8m3edFjGO69/9eecI5EczRxuU8AvsoTVPRjCIpDkpKJuOej8mmOZN7aTkJtahANKFc5X8Xii7Fc6xpU1Dqpl2/eG6VPR7LNJ2+Lxx0vy7PofC2jO7P95F9Fe/J/42FJYzfXx6P1fCeUq2KkYKaDQYWLrEnwfIBm5JE943BzhuEodlY1aqxcc6ZMvwonBQL8o8Bz6rqz4bbPwV8t6p+vPSYjwEfCze/HfjK2z7Qx8M54O4DH3VymKf5zNNc3quqS4d5osveicDncjxxudvLPH2+PpfjyYHk7qRYkGXKfeOGRtVPAZ8CEJG/Ogq31XFgnuYC8zWfeZvLYZ/rsnf88bkcT1zu9uJzOZ7M21wO8riTUovqOnCtdPsq8OaMxuI4juM4juPMMSdFQX4OeI+IvEtEasA/A/5wxmNyHMdxHMdx5pATEWKhqomIfBz4Y6zM22+o6t/e5ymfentG9rYwT3OB+ZqPz+XxXec44HM5nvhcHt91jgM+l+PJqZvLiUjScxzHcRzHcZy3i5MSYuE4juM4juM4bwuuIDuO4ziO4zhOiblTkEXkWRH5moi8LCL/etbjOSwi8hsicltETnxtSxG5JiJ/LiJfFZG/FZFPzHpMh0VEGiLylyLyQpjLv5/1VryKFwAABWJJREFUmB4VEYlF5G9E5H8+wjXmQu5gfmTP5e5443I3jsvd8WTeZO9h5G6uFOTQkvq/Aj8EPAP8uIg8M9tRHZrfBJ6d9SCOiAT4l6r6NPAh4F+c4M+lD3xEVb8TeB/wrIh8aMZjelQ+AXz1sE+eM7mD+ZE9l7vjjcvdOL+Jy91xZN5k78ByN1cKMqWW1Ko6APKW1CcOVf0CsDHrcRwFqnpTVf86/L2DfTmvzHZUh0ONdrhZDT8nNtNVRK4CPwx8+hEuMzdyB/Mjey53xxeXu7243B1P5kn2Hlbu5k1BvgK8Ubp9nRP8xZxHROSdwHcBfzHbkRye4KJ5HrgNfF5VT+xcgP8M/Csge4RruNwdc1zujh0ud6eAeZA7mCvZeyi5mzcF+YEtqZ3ZISKLwB8Av6Cq27Mez2FR1VRV34d1dPygiHz7rMd0GETkR4DbqvqlR73UlPtc7o4JLnfHC5e708G8yB3Mh+wdRu7mTUH2ltTHFBGpYovF76jqZ2c9nqNAVbeA/8XJjZv7MPCjIvIa5p79iIj89iGu43J3THG5O5a43M058yh3cOJl76Hlbt4UZG9JfQwREQF+Hfiqqv7HWY/nURCR8yKyGv5uAj8I/N1sR3U4VPWXVPWqqr4Tk5U/U9WfPMSlXO6OIS53xxOXu/lmnuQO5kf2DiN3c6Ugq2oC5C2pvwr83gNaUh9bROR/AF8E3isi10XkZ2Y9pkfgw8BPYSe258PPP5n1oA7JZeDPReRFbIP6vKoeukzTPDBPcgdzJXsud3OMy92xZZ7kDk6x7HmracdxHMdxHMcpMVcWZMdxHMdxHMd5VFxBdhzHcRzHcZwSriA7juM4juM4TglXkB3HcRzHcRynhCvIjuM4juM4jlPCFWTHcRzHcRzHKeEKsoOInC3Va3xLRG6Ubv+/x/B6Py0id0Tk00d4zY+KyMsicirqMzonH5c7x5kNLnvOQajMegDO7FHVdeB9ACLy74C2qv6Hx/yyn1HVjx/VxVT1MyJyC/jFo7qm4zxOXO4cZza47DkHwS3Izn0RkXb4/X0i8r9F5PdE5Osi8ssi8hMi8pci8mUReSo87ryI/IGIPBd+PnyA1/gH4TrPi8iLIvKecP9Plu7/VRGJw/3Pishfi8gLIvKnj3P+jjMLXO4cZza47Dk5bkF2HobvBJ4GNoBXgE+r6gdF5BPAzwG/AHwS+E+q+n9F5AmsDerTD7juPwc+qaq/IyI1IBaRp4GPAh9W1aGI/ArwEyLyR8CvAf9IVV8VkbXHMVHHOUa43DnObHDZO8W4guw8DM+p6k0AEfl74HPh/i8D3x/+/kHgGRHJn7MsIkuqunOf634R+DcichX4rKp+Q0R+AHg/8Fy4VhO4DXwI+IKqvgqgqhtHNjvHOZ643DnObHDZO8W4guw8DP3S31npdsbouxQB36Oq3YNeVFX/u4j8BfDDwB+LyM8CAvyWqv5S+bEi8qOAHnL8jnMScblznNngsneK8Rhk56j5HFAkIojI+x70BBF5N/CKqv4X4A+Bfwj8KfBjInIhPGZNRJ7ETt7fKyLvyu8/+ik4zonD5c5xZoPL3pziCrJz1Pw88IGQePASFmv1ID4KfEVEnge+DfhvqvoS8G+Bz4nIi8Dngcuqegf4GPBZEXkB+MxjmYXjnCxc7hxnNrjszSmi6pZ75+1FRH4a+MBRlrwJ1/0+4BdV9UeO8rqOMw+43DnObHDZO5m4BdmZBV3gh+SIi6YDvwJsHtU1HWfOcLlznNngsncCcQuy4ziO4ziO45RwC7LjOI7jOI7jlHAF2XEcx3Ecx3FKuILsOI7jOI7jOCVcQXYcx3Ecx3GcEv8fMiNzk3vzE+YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x216 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#%% Plot magnitude spectrogram of 3 wav files\n",
    "fig = plt.figure() \n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10,3), sharey=True)\n",
    "\n",
    "ax1.pcolormesh(tmixed, fmixed, np.abs(Zmixed_series))\n",
    "ax1.set(title='Mixture signal', xlabel='Time [sec]', ylabel='Frequency [Hz]')\n",
    "\n",
    "ax2.pcolormesh(t1, f1, np.abs(Zsamples1))\n",
    "ax2.set(title='Signal 1', xlabel='Time [sec]')\n",
    "\n",
    "ax3.pcolormesh(t2, f2, np.abs(Zsamples2))\n",
    "ax3.set(title='Signal 2', xlabel='Time [sec]')\n",
    "\n",
    "plt.tight_layout()\n",
    "#fig.savefig(\"spectrograms.png\", bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "plt.close(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Create IBM for signal 1 by calculating SNR of signal 1 vs mixture signal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A mask was then calculated using the SNR of the absolute value of the STFT of the clean signal of one of the speech signals (speaker 2) divided by the absolute value of the STFT of the mixture signal. An IBM was created rounding this mask to the nearest integer and then applying a ceiling function so that any number greater than 1 was given the value 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.1628723 , 0.33648875, 0.4496353 , ...,        nan,        nan,\n",
       "               nan],\n",
       "       [0.15258941, 0.40417036, 0.41113153, ...,        nan,        nan,\n",
       "               nan],\n",
       "       [0.20557386, 0.67476964, 0.5124027 , ...,        nan,        nan,\n",
       "               nan],\n",
       "       ...,\n",
       "       [0.528545  , 0.7404754 , 1.2975628 , ...,        nan,        nan,\n",
       "               nan],\n",
       "       [0.47411957, 1.2847348 , 0.9551614 , ...,        nan,        nan,\n",
       "               nan],\n",
       "       [0.48634914, 7.549913  , 1.544811  , ...,        nan,        nan,\n",
       "               nan]], dtype=float32)"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# Calculate signal to noise ratio of clean signal versus combined signal (for speaker 2)\n",
    "snr2 = np.divide(np.abs(Zsamples2), np.abs(Zmixed_series))  # dividing denominator may be 0, so there will be nan\n",
    "snr2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  0.,  0., ..., nan, nan, nan],\n",
       "       [ 0.,  0.,  0., ..., nan, nan, nan],\n",
       "       [ 0.,  1.,  1., ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [ 1.,  1.,  1., ..., nan, nan, nan],\n",
       "       [ 0.,  1.,  1., ..., nan, nan, nan],\n",
       "       [ 0.,  8.,  2., ..., nan, nan, nan]], dtype=float32)"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Round snr to 0 or 1 to create binary mask\n",
    "mask2 = np.around(snr2, 0)\n",
    "mask2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 0., 0., ..., 1., 1., 1.],\n",
       "       [0., 0., 0., ..., 1., 1., 1.],\n",
       "       [0., 1., 1., ..., 1., 1., 1.],\n",
       "       ...,\n",
       "       [1., 1., 1., ..., 1., 1., 1.],\n",
       "       [0., 1., 1., ..., 1., 1., 1.],\n",
       "       [0., 1., 1., ..., 1., 1., 1.]], dtype=float32)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert all nan in mask to 1 (it shouldnt matter if this is 0 or 1)\n",
    "mask2[np.isnan(mask2)] = 1\n",
    " \n",
    "# Replace all values over 1 with 1\n",
    "mask2[mask2 > 1] = 1\n",
    "mask2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check to see what maximum value in array is\n",
    "np.amax(mask2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Speech recovery"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The mixture signal is then combined with the mask using element-wise multiplication (Hadamard product). An iSTFT is then applied to the resulting array to obtain the original speech signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Computer two masks of two speakers\n",
    "mask1 = 1 - mask2  # speaker 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Element-wise multiply mask with mixed signal t-f signal\n",
    "Zsamplesmaked1 = np.multiply(Zmixed_series, mask1)\n",
    "Zsamplesmaked2 = np.multiply(Zmixed_series, mask2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show mask\n",
    "fig = plt.figure()\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(11, 8), sharey=True)\n",
    "\n",
    "ax1.imshow(mask1, cmap='Greys', interpolation='none')\n",
    "ax1.set(title='Mask1', xlabel='Time [sec]', ylabel='Frequency [Hz]')\n",
    "\n",
    "ax2.imshow(mask2, cmap='Greys', interpolation='none')\n",
    "ax2.set(title='Mask2', xlabel='Time [sec]', ylabel='Frequency [Hz]')\n",
    "\n",
    "#fig.savefig(\"masks.png\", bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "plt.close(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert back to a time series via inverse STFT, uses the phase spectrum of the mixed speech\n",
    "_, samplesrec1 = signal.istft(Zsamplesmaked1, sample_rate1)  # speaker 1\n",
    "_, samplesrec2 = signal.istft(Zsamplesmaked2, sample_rate2)  # speaker 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Play the recovered speech1\n",
    "sd.play(samplesrec1, sample_rate1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Play the recovered speech2\n",
    "sd.play(samplesrec2, sample_rate2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare the original wav with recovered wav (speaker 1)\n",
    "fig = plt.figure()\n",
    "plt.plot(x, samples1, color=\"red\", alpha = 0.6)\n",
    "plt.plot(x, samplesrec1, color=\"blue\", alpha = 0.4)\n",
    "plt.title(\"Recovery for speaker 1\")\n",
    "plt.xlabel('Time [sec]')\n",
    "plt.ylabel('Signal')\n",
    "plt.legend(['Original', 'Recovered via STFT'])\n",
    "\n",
    "#fig.savefig(\"recoverd1.png\", bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "plt.close(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare the original wav with recovered wav (speaker 2)\n",
    "fig = plt.figure()\n",
    "plt.plot(x, samples2, color=\"red\", alpha = 0.6)\n",
    "plt.plot(x, samplesrec2, color=\"blue\", alpha = 0.4)\n",
    "plt.title(\"Recovery for speaker 2\")\n",
    "plt.xlabel('Time [sec]')\n",
    "plt.ylabel('Signal')\n",
    "plt.legend(['Original', 'Recovered via STFT'])\n",
    "\n",
    "#fig.savefig(\"recoverd2.png\", bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "plt.close(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
